Our world is constantly
shifting and transforming. Companies everywhere are
working to lead the way to the next big thing, and consumers expect rapid,
exciting product launches and packages that are delivered to their doorsteps like magic. With all of this incredible change, the value of speed has
become immeasurable. It’s truly one of the
most important factors of business success today. After all, the ability to identify an issue or
opportunity is great, but real value is achieved
when you identify that issue before it becomes a huge problem, or act upon that opportunity
ahead of the competition. These days, there’s more data about marketplaces, organizations, customers, competitors, and
employees than ever before, but we need more than data alone to make better decisions
and deliver rapid results. And that’s where intelligence comes in… business intelligence. Business intelligence, or BI, involves automating processes
and information channels in order to transform relevant
data into actionable insights that are easily available
to decision-makers. In other words, by showing decision-makers what is currently happening, organizations become more
intelligent and successful. A national restaurant group might analyze millions of customer receipts to optimize its food
supply and reduce waste, or a local hospital could integrate numerous different data sources to review feedback and outcomes in order to help personalize
the patient experience, or perhaps a global manufacturing company uses supply chain data
from around the world to make more precise demand forecasts and ensure appropriate inventory levels. The BI applications are endless, and so are the BI career opportunities. The field involves such diverse
organizations and industries, that wherever your interest may be, there’s a path for you. In this program alone, you’ll learn about everything from appliance
manufacturers to grocery stores to local artisans to artificial
intelligence companies. BI professionals are making
an impact everywhere. As for me, my name is Sally, and I’m a Business
Intelligence Analyst at Google. I’m thrilled to welcome you to the Google Business
Intelligence Career Certificate. I’ll be your instructor for the first course of this program. Completing a Google Career
Certificate like this one will help you develop relevant skills that employers are looking for when hiring business intelligence talent. You’ll learn how to use the tools of a fast-growing, high-paying
field, and when you graduate, you can connect with hundreds
of employers in the US who are interested in hiring Google Career Certificate graduates. The program is designed
to prepare you for a job in three to six months, if you work on the certificate part-time. And it’s really flexible. There are just three courses, which you’ll complete on your own terms, at your own pace, all online. Whether you’re seeking to
switch careers, find a new job, level up your skills, or build a business, Google Career Certificates can open doors to new opportunities. You might know me from the Google Data
Analytics Certificate, which is a key foundation
for this program. What you will learn here
relies on that foundation, so you wanna be sure to
earn that certificate first or use our upcoming self-assessment to ensure you have comparable knowledge. I’ll be by your side
throughout this first course, making sure that you’re learning
what you need to succeed. I love the world of BI and
really enjoy working with SQL and digging into the
technical side of analytics in support of Google’s People Operations. This team is dedicated to
Google staffing, development, and a distinct and inclusive culture. But I didn’t start out in BI. When I first thought about
my professional path, I was interested in becoming a physician, but I ended up really enjoying
the biological sciences so I thought I’d be a
biomedical researcher. Of course, data analytics
is the science of data, so it kind of made sense that this field ended up peaking
my interest along the way. I started my career as
an analyst and here I am. That’s just one example, and everyone’s experience is different. In fact, the Google Career
Certificates were designed by industry professionals
with decades of experience, and you’ll have a different
expert from Google to guide you through each course. We’ll share our knowledge in videos, help you practice with
hands-on activities, and take you through scenarios that you might encounter on the job. First, meet my teammate, Ed. Hello, I’m Ed, and I’m a
product manager at Google. Together, we’ll explore
data modeling and ETL, which stands for extract,
transform, and load. It’s all about getting data
where and how you need it so you can analyze and monitor it. Next, you’ll meet Terrence. Hey there, I’m Terrence, and I’m a Senior Business
Intelligence Analyst. I’m really looking forward
to spending time with you as you discover how to apply your understanding of stakeholder needs when creating BI visualizations. We’ll also use dashboards
to present clear insights that can advance all kinds of companies. Hi, I’m Anita, and I’m a Senior Business
Intelligence Analyst here at Google. I’ll guide you through different career-building
topics and activities, including the end-of-course project, featuring portfolio creation. A portfolio is a collection of materials that can be shared with
potential employers. This exciting hands-on
experience will bring together everything you learned during this program and enable you to apply your skills to a realistic business scenario. We’re all really glad you’re here, and I, for one, can’t wait to get started. Are you ready to take the first step towards joining us in the BI profession? Let’s go!

There are an endless
number of reasons to pursue a career in
business intelligence. Enjoying analytical thinking
or having an interest in numbers are wonderful
motivations for becoming a BI professional. But there’s so much more
to the world of BI. Maybe you’re passionate
about solving problems, simplifying processes, or removing
pain points for others. Perhaps you have great
communication skills, and you’d like to use them to share insights and help your team make
effective decisions. Lots of people in BI enjoy
creating tools that streamline tasks and enable
their colleagues to devote more time
to other projects. BI professionals are
inspired in all kinds of ways. But when I talked to my
colleagues here at Google, the thing they love
most is simply using their talents to
make other people happy. There’s a lot of satisfaction
in knowing that you’ve made someone’s job easier or saved them a bunch of
time. And right now, you’ve made me happy
because you’re here to explore the exciting and
rewarding career path, the BI. In this first course, you will begin learning
about the BI industry. If this is new
territory for you, you’ll discover how to
identify the career path and employer type that best suits
your skills and interests. You’ll also consider
the roles of BI analysts versus BI engineers. If you already have
some BI experience, we’ll open new doors to more fascinating
career opportunities. You’ll understand how to develop a BI project that
makes an impact. You’ll be introduced to BI tools and techniques that
professionals use every day for making business decisions and
improving processes. The similarities and differences between BI and data
analytics will be clarified. And together we will
explore the importance of context when working
with data and learn how to overcome
some common limitations, such as human bias. Then throughout the program, you’ll continue
gaining new skills. You will use data
modeling to design data storage systems
such as data warehouses, data marts, and data lakes. You apply data pipelines
and the ETL process. Designing and
interpreting dashboards will be an essential
part of your learning, as well as communicating with stakeholders about
your findings. Finally, you’ll prepare for your job search by developing
a personal strategy, growing your
professional network, and preparing materials. Most of the content in
this program builds upon core data
analytics concepts. If you have some
experience in that area, or if you earned your Google
Data Analytics certificate, then you’ve definitely
come to the right place. If you’re unsure about having the necessary prerequisites
for this program, there’s an ungraded
assessment coming up soon to evaluate your readiness. In addition, we’ll include
helpful resources from the Google Data Analytics certificate throughout
each course, which you can use to
review key concepts. Let’s start building your
BI skills and knowledge. Continue to the next lesson
to keep the momentum going.

Hi, I’m Sally. I’m a Business Intelligence Analyst
at Google. What that means is, I work with data to help improve
the hiring experience at Google. The way in which I entered data analytics
is via a business boot camp that I did years ago. I was thinking of
becoming biomedical researcher and this is something I just wanted
to use during extra time that I had. We learned about just data
analysis in general and I found that I had like a knack for it. Everything just made sense. It was very tangible. You can see the results pretty immediately
and you could search for things. I love puzzles, so
trying to find using different clues and trying to find what is the answer. And I really enjoyed it as well
as enjoyed working with teams, which is different from
when I was in the sciences. It was very much independent,
I was doing my own thing. But within the business boot camp,
I was working within a group of people and that was so social and so much fun. And we were supporting each other and
I love that, that team environment. Through the program is
how I got my first job. There was someone I met on the program
who graduated a year before me. And when it was time for me to apply for
jobs, he had an opening on his team and he reached out to me to
see if I wanted to apply. So that’s actually how I
got into data analytics. I didn’t study data analytics. I had to teach myself everything from,
I had to teach myself SQL. I didn’t feel like I was
really contributing or that I had any security in this field. And so what I tried to do is I
try to teach myself python, go into machine learning, and what not. But ultimately, what I found is,
I don’t need to do that. I just need to find a niche – what
I’m good at – and develop that and become an expert in that. So the advice that I would give for someone who’s trying to enter the field
of business intelligence, is to consider the difference between
data analytics and business intelligence. I personally found that
I really like SQL. Love SQL on the technical
side of things. In addition to that, so I wanted to level
up and enter business intelligence. You can make your career within
the broader field of data analytics be whatever you want,
depending on what it is that you enjoy.

We often hear about all of the data that’s created
each and every day. It could be something
as simple as taking a photo with your phone
or paying your bills, or something as complex as
a global company launching a new product or running a multimedia
advertising campaign. It really feels like practically
everything creates data. So it’s no wonder that
organizations need experts to help them
access the right data, use it to find ways to grow and improve, and put those
insights into action. In fact, as the volume
of data is ever escalating so is a need for professionals who can
make that data shine. For instance, in my role, I’m proud to be
able to use data to give my stakeholders
a quick overview of exactly what they need to know without getting
lost in the details. The tools I create enable them to clearly evaluate
the candidate hiring and employee experiences within Google’s
People Operations. One way this works is by showing
my stakeholders how long the interview journey is when someone is being
hired at Google. This is important because it helps them determine
if we need to hire more recruiters or
interview schedulers in order to improve the
process for our candidates. In this video, you’ll learn more about how those
of us in BI offer value to our colleagues
and how we help shape the future of
our organizations. There are so many different
potential roles to explore. For example, in this program, you’ll learn a lot about BI
analysts and BI engineers. BI analysts gather requirements
from stakeholders, partners, and team members. They use their understanding of large datasets to retrieve, organize, and interpret data. Then they create
visualizations, dashboards, and reports to use when presenting and communicating
insights to others. The intelligence they share might be used to make decisions, develop a new process, or create a business strategy, or it could be applied
to even deeper analysis. BI engineers are
responsible for designing, configuring, implementing, and improving data
tools and processes. They evaluate and
streamline various devices, infrastructures, and information channels
called pipelines. Engineers are excellent
troubleshooters and help find solutions
to security issues, application permissions
and updates, and other technical challenges. In other words, a BI engineer manages tools and processes, which enables a BI analyst to put those tools and
processes to work. However, it’s also
important to note that some companies
don’t distinguish between those two BI jobs, using the terms analyst and
engineer interchangeably. So when you begin to explore
job opportunities, be sure to spend some time
researching the job and organization in order to fully understand
what’s involved. No matter which path
you ultimately choose, a career in BI has a
potential to be amazing. Research shows that
all industries today need skilled
BI professionals. But there are not
enough people with the right experience and
talent to satisfy this demand. BI professionals enjoy
strong career prospects. In fact, a quick search for
job openings in the industry reveals thousands of
opportunities on LinkedIn alone. But perhaps best of all, BI professionals find the work rewarding and fulfilling because we know what we do makes
someone else’s life better. Coming up and throughout
this program, you’ll discover some really
inspiring examples of just how BI makes such
a positive impact. I can’t wait to
share them with you.

1. Learn about the different roles in business intelligence. There are many different roles in business intelligence, each with its own set of responsibilities. Some of the most common roles include:
   • BI analyst: BI analysts gather and analyze data to help businesses make better decisions.
   • BI engineer: BI engineers design, build, and maintain data pipelines and BI tools.
   • BI developer: BI developers create and maintain BI applications.
   • BI manager: BI managers oversee the BI team and ensure that the BI function is aligned with the business goals.
2. Identify the skills and experience you need for a BI career. The specific skills and experience you need for a BI career will vary depending on the specific role you are interested in. However, some of the most common skills include:
   • Data analysis skills
   • Data visualization skills
   • SQL skills
   • Business intelligence tools
   • Programming skills
   • Communication skills
   • Problem-solving skills
3. Network with people in the BI field. Networking is a great way to learn about BI careers and meet people who can help you get started. Attend industry events, join online forums, and connect with people on LinkedIn.
4. Get certified. Getting certified can demonstrate your skills and knowledge to potential employers. There are many different BI certifications available, so choose one that is relevant to the role you are interested in.
5. Start building your portfolio. A portfolio is a great way to showcase your skills and experience to potential employers. Include projects you have worked on, visualizations you have created, and any other relevant work.
6. Apply for jobs. Once you have the skills, experience, and portfolio, you can start applying for BI jobs. Be sure to tailor your resume and cover letter to each specific job you apply for.
7. Don’t give up. The job search can be tough, but don’t give up. Keep learning and growing, and eventually you will find the right BI career for you.

Here are some additional tips for exploring business intelligence careers:

• Take some online courses or tutorials on data analysis and visualization.
• Volunteer your data analysis skills to a local organization.
• Build a personal website or blog to showcase your work.
• Attend industry conferences and meetups.
• Network with people on LinkedIn and other social media platforms.

What do you do when you’re facing
a really challenging task or big problem? You’ve done your research,
tried multiple approaches, but nothing seems to be working. It’s natural to be frustrated. We’ve all been there. But a much better strategy
is to simply ask for help. As the saying goes,
two heads are better than one. And in business complex
problems often require 5, 10, or even hundreds of people
coming up with potential solutions. This is why business intelligence
professionals collaborate with lots of different team members in their work.
Brainstorming and building together, pulling knowledge, and working out
issues is essential to the BI process. BI professionals also rely
on team members to provide important inputs for their projects and
to partner on solutions. This video will share examples of
the key players you might work with. Keep in mind every organization handles
job titles differently, so you may encounter some discrepancies or overlap,
but this is a great place to start. First up, API professionals. API stands for
application programming interface. This is a set of functions and procedures
that integrate computer programs forming a connection that
enables them to communicate. There are so
many different roles that involve APIs. Including API strategists, developer, engineer, and product owner. When you’re working in business
intelligence, you might collaborate with API professionals in order to create the
interface that you need for a particular project, especially if some of your data
is coming from a third party platform. APIs bring that data into the internal
company database in order to build reporting tools and dashboards. API professionals code in a number
of different computing languages including Python, Java, and so many others. So it’s up to API partners to write
code that’s specific to each project and business need. You may work with data warehousing
specialists who develop processes and procedures to effectively store and
organize data. These people also help ensure BI
professionals can easily access the data they need. There are also data
governance professionals. These team members are responsible for the formal management of
an organization’s data assets. This may involve managing
the availability, integrity, and security of data based
on internal standards and policies. This is very important for
making sure data is trustworthy and doesn’t get misused or corrupted. Of course data analysts are key
partners as they collect, transform and organize data. They are dataset specialists reviewing
and validating the data all the time. They also identify and implement
exciting new analysis methodologies. Another key team is IT. Information technology professionals test
install, repair, upgrade, and maintain the hardware and software solutions
that organizations use every single day. BI professionals work with the IT department in order to maximize all of the available data and data tools. In addition, project managers are key
collaborators, as they handle the day-to-day project steps, scope, schedule,
budget, resources, and much more. There are all kinds of contributors and
every organization is different. Who you work with will depend on the size of
the company, the available tools, and the nature of the work. For example, if your project deals
with the customer experience, then the customer success team will
be essential to providing inputs. If your project is about
employee engagement, then you’ll work closely with the HR team. And because my work involves hiring
processes, I really benefit from collaborating with the recruiting
team members here at Google. Now, there is another essential
group of people on the team and that’s your stakeholders.
In an upcoming section in this course, we’ll talk lots more about the various
stakeholder roles as they relate to BI. We’ll also explore different stakeholder
goals and how you can use your BI skills to reach them. Stay tuned.

What is a business intelligence team?

A business intelligence (BI) team is a group of people who work together to collect, analyze, and visualize data in order to help businesses make better decisions. The specific roles and responsibilities of a BI team will vary depending on the organization, but some common roles include:

• BI analysts: BI analysts gather and analyze data to identify trends and patterns. They also create reports and dashboards to communicate their findings to stakeholders.
• BI developers: BI developers design, build, and maintain BI applications. They also work with BI analysts to ensure that the applications meet the needs of the business.
• BI architects: BI architects design the overall BI architecture for the organization. They also work with other IT teams to ensure that the BI infrastructure is scalable and secure.
• BI managers: BI managers oversee the BI team and ensure that it is meeting the needs of the business. They also work with other stakeholders to identify and prioritize BI projects.

Who are the key partners of a business intelligence team?

In addition to the members of the BI team, there are a number of other people who are important partners in the BI process. These partners include:

• Data scientists: Data scientists use advanced statistical and machine learning techniques to extract insights from data. They can be valuable partners for BI teams in developing predictive models and other advanced analytics.
• IT professionals: IT professionals are responsible for the hardware and software that the BI team uses. They can help the BI team to select the right tools and technologies, and they can also help to troubleshoot problems.
• Business users: Business users are the people who will ultimately use the BI team’s insights. They can provide valuable feedback to the BI team on the usability and effectiveness of the BI applications.
• Stakeholders: Stakeholders are the people who are affected by the BI project. They can include executives, managers, and other employees. Stakeholders can provide valuable input to the BI team on the goals of the project and the metrics that should be used to measure success.

How do business intelligence teams and partners collaborate?

The success of a BI project depends on the effective collaboration of the BI team and its partners. This collaboration should be based on a shared understanding of the business goals, the data that is available, and the tools and technologies that can be used. The BI team should work closely with data scientists, IT professionals, business users, and stakeholders to ensure that the BI project is successful.

Here are some tips for effective collaboration between BI teams and partners:

• Establish clear communication channels. The BI team should establish clear communication channels with its partners. This can be done through regular meetings, email, or other means.
• Share information openly. The BI team should share information openly with its partners. This includes sharing data, reports, and other insights.
• Be responsive to feedback. The BI team should be responsive to feedback from its partners. This feedback can help the BI team to improve the quality of its work.
• Build trust. The BI team should build trust with its partners. This can be done by being open and transparent, and by delivering on its promises.

By following these tips, BI teams can collaborate effectively with their partners to deliver valuable insights that can help businesses to make better decisions.

Which business intelligence team members are responsible for the formal management of an organization’s data assets?

Data governance professionals

Data governance professionals are responsible for the formal management of an organization’s data assets. This may involve managing the availability, integrity, and security of data based on internal standards and policies.

With business intelligence and data analytics gaining so
much popularity these days, the term business
intelligence and data analytics are often
defined incorrectly, oversimplified, or used interchangeably for
speedy communication. That can lead to
confusion because BI and DA are quite different. In this video, we’re
going to sort that out. First, let’s establish
that both BI and DA professionals enable data-driven decision-making
in their organizations. They’re also both a key part of their company’s
data maturity. Data maturity is the extent to which an
organization is able to effectively use its data in order to extract
actionable insights. Whether that data includes information about
your customers, staff, products, suppliers,
finances, or something else, it’s worthless if it
can’t be put to work. Putting data to work requires skilled professionals
who can apply techniques and technologies to achieve high levels of maturity. In this effort, data
analysts are primarily involved with using data to answer questions
about what happened. On the other hand,
BI professionals aim to achieve higher levels of data maturity by building data reporting tools
such as dashboards. Dashboards continuously
analyze and monitor data. The work isn’t complete just because the tool
has been created. The analysis and monitoring are ongoing. This is
because BI involves establishing repeatable methods
to understand how things are operating and by
knowing the current state, company leaders can take action to improve
the future state. For example, a BI
professional might investigate what
new sales prospects are being targeted today. How many customers have
we gained this month? Or did our weekly email perform well with new subscribers? Because BI is all about
near-real-time rapid monitoring, BI insights are most effective when they make an
impact right now. Therefore, the people who use the reporting tools
wants to make sure they are practical
and efficient. BI professionals are
expert tool builders. Then it’s typically
the data analysts who apply these tools
in order to answer a question or solve a problem by examining the data through
a specific topic or lens. Again, a big part of BI is
creating dashboards that provide users with clear
snapshots of the current state. These tools must be impactful
and easy to interpret. Even for non-technical people. If you like thinking
about what you can create that meets the needs
of many different users, BI will let you do just that. BI professionals
generally work on large scale projects that are helpful for multiple
stakeholders. Also, as you consider how you
will fit in the BI world, note that BI professionals
are experts in data infrastructure and enjoy the technical side
of data analytics. For instance, if
you love working with databases, big data, and the computer
programming language SQL, BI will give you the opportunity to take your queries
to the next level. If you earned the Google Data
Analytics certificate, the content included
there formed your foundational
knowledge and experience. Now, this BI program
will provide a complimentary skill set that builds on
those foundations. It will also add a lot of very marketable talents to
your resume that will create a compelling combination
of skills for employers to consider and will open the doors for more
job opportunities. In addition to the
technical side of things such as managing
large datasets, writing queries in SQL,
and creating dashboards. You’ll learn some really
worthwhile professional skills. These include: the
ability to juggle many different priorities,
attention to detail, owning a process,
communicating with others, and learning how to go beyond
surface level requests. Perhaps most importantly, you’ll discover the
value of connecting with others to really drive
results and that’s how you build a career rather
than just have a job. In future lessons, you
will continue to explore the similarities and
differences between BI and DA. The two disciplines complement
and rely on each other. Just like the talented people
who work in these roles. Together, they help
their organizations advance on the data
maturity scale every day.

1. Collect and store data. The first step is to collect and store data from a variety of sources, such as customer transactions, social media, and sensor data. This data can be structured or unstructured, and it can be stored in a variety of ways, such as in a data warehouse or a data lake.
2. Clean and prepare the data. Once the data is collected, it needs to be cleaned and prepared for analysis. This involves removing errors, filling in missing values, and transforming the data into a format that can be easily analyzed.
3. Analyze the data. The data can be analyzed using a variety of statistical and machine learning techniques. The goal of the analysis is to identify patterns and trends in the data that can be used to make informed decisions.
4. Visualize the results. The results of the analysis can be visualized using charts, graphs, and dashboards. This makes it easier to understand the results and to communicate them to others.
5. Take action. The final step is to take action based on the results of the analysis. This could involve making changes to products or services, developing new marketing campaigns, or improving customer service.

BI can maximize the value of data analytics by providing a framework for collecting, storing, cleaning, analyzing, visualizing, and acting on data. By following these steps, organizations can gain insights from their data that can help them make better decisions and improve their bottom line.

Here are some additional tips for maximizing the value of BI and data analytics:

• Make sure that the data is accessible to the people who need it.
• Train employees on how to use BI and data analytics tools.
• Create a culture of data-driven decision-making.
• Share the results of the analysis with stakeholders.
• Use BI and data analytics to improve processes and optimize operations.

By following these tips, organizations can get the most out of their BI and data analytics investments.

When helping their organizations achieve data maturity, business intelligence professionals are typically responsible for which of the following tasks? Select all that apply.

• Building data-reporting tools and dashboards
• Working on large-scale projects that are helpful to multiple stakeholders
• Establishing repeatable methods for monitoring data

Business intelligence professionals are typically more involved with building data-reporting tools and dashboards, establishing repeatable methods for monitoring data, and working on large-scale projects that are helpful to multiple stakeholders.

If you earned your Google
Data Analytics certificate, then you’re very familiar with the data life cycle and
the data analysis process. Data analysts use these phases in their work every single day in order to gain insights that lead to informed decision-making. As a quick refresher, the data life cycle
is a sequence of stages that data experiences, which include plan, capture, manage, analyze,
archive, and destroy. The data analysis process
occurs in six phases. Ask, prepare, process,
analyze, share, and act. Business intelligence
also has phases, a sequence of three stages that determines the value of BI, as well as organizational
data maturity. As you’ve learned,
data maturity is a meaningful goal for
any BI team because high maturity means
their organization is effectively using
its data in order to extract actionable insights. In BI, the three stages are capture, analyze, and monitor. As you advance through each one, the process requires
a deeper level of exploration and investigation, so each becomes more complex. These phases might be
automated or done manually, but each one adds
significant business impact, which is well worth the effort. It’s important to
understand these stages and how they can benefit you
as a BI professional. We’re going to explore each
one of them in this video. Let’s start with capture, which is the “what happened”
point in the BI process. This stage pertains to static backward-looking
data. For instance, if you were to query a
database to return a data set about what your customers
purchased last month, that’s an example of
capturing information. Or you might access a
spreadsheet that lists profits and losses from
the previous quarter. That’s also an example of capturing or record of
certain information. Records are essential to BI, but they don’t enable
users to easily investigate in depth and
really dig into the data, and that hinders the insights
they’re able to provide. Also, because of
data in this stage is rigid and backward-looking, it’s not always very useful for proactive
forward-looking decisions. Capturing information is a
necessary element of BI, but information alone doesn’t let us know what’s working well, how we can improve
or what to do next. However, in the following step, things get better. Which brings me to Stage 2: analyze. The “why did it
happen” part of BI. You already know a
lot about this stage, but as a quick reminder, data analysis is when
we draw conclusions, make predictions, and drive
informed decision-making. Because the analyze stage
explorers why things happen, it’s much more
likely to result in effective plans and strategies. In this way, it enables
BI professionals to better understand key
relationships between data points. They do this by examining data
more deeply, more broadly, or even side-by-side,
in order to identify connections that at first
might not have been apparent. Now we’ve come to
the final part of the process: monitor. Monitor is the “what’s
happening now” stage, and here’s where
BI professionals really get to show off their
unique skills and expertise. In this stage, you use automated processes and
information channels, such as data models, ETL pipelines,
dashboards and more. These exciting tools take the data that
organizations create every single day and
transform it into true intelligence that is easily available
to stakeholders. These BI tools reveal upswing, downturns, changes, challenges, opportunities,
and much more. Decision-makers then use
the insights these tools deliver in order to proactively work
towards business goals. You’ll learn all about these BI tools in
upcoming courses, and soon in this course, I’ll provide some
foundational information about the BI
professional’s toolbox. You can use it to
start familiarizing yourself with what happens
during the monitor stage. For now, great job on all the progress
you’ve made so far. I’m so happy to be sharing
the world of BI with you. Let’s keep it up and
head to the next lesson.

• Stage 1: Capture

The first stage of BI is to capture data from a variety of sources, such as databases, spreadsheets, and social media. This data can be structured or unstructured, and it can be collected in real time or historical.

• Stage 2: Prepare

Once the data is captured, it needs to be prepared for analysis. This involves cleaning the data, removing errors, and filling in missing values. The data may also need to be transformed into a format that can be easily analyzed.

• Stage 3: Analyze

The third stage of BI is to analyze the data to identify trends, patterns, and relationships. This can be done using a variety of statistical and machine learning techniques.

• Stage 4: Visualize

The results of the analysis can be visualized using charts, graphs, and dashboards. This makes it easier to understand the results and to communicate them to others.

• Stage 5: Act

The final stage of BI is to act on the results of the analysis. This could involve making changes to products or services, developing new marketing campaigns, or improving customer service.

The stages of BI are not always linear. In some cases, it may be necessary to go back and forth between stages. For example, if the analysis reveals that the data is not clean enough, it may be necessary to go back to the prepare stage.

The BI process can be automated or done manually. Automated BI tools can help to speed up the process and make it more efficient. However, manual BI can be more flexible and can be tailored to the specific needs of the organization.

BI is a valuable tool for businesses of all sizes. It can be used to improve decision-making in all areas of a business, such as marketing, sales, operations, and finance.

Here are some additional tips for implementing BI in your organization:

• Start with a clear understanding of your business goals. What do you hope to achieve by using BI?
• Identify the data that you need to collect. What data will help you to achieve your goals?
• Choose the right BI tools. There are a variety of BI tools available, so it is important to choose the ones that are right for your needs.
• Train your employees on how to use the BI tools. BI tools can be complex, so it is important to make sure that your employees know how to use them effectively.
• Communicate the results of the BI analysis to stakeholders. The insights from BI can only be helpful if they are communicated to the people who need them.

By following these tips, you can implement BI in your organization and start to reap the benefits of data-driven decision-making.

Fill in the blank: The business intelligence stages of capture, analyze, and monitor help determine BI’s business value, as well as an organization’s _____.

data maturity level

The business intelligence phases of capture, analyze, and monitor help determine BI’s business value, as well as an organization’s data maturity level. Data maturity is the extent to which an organization is able to use its data in order to extract actionable insights.

Strategy is a big part of life in so
many ways. Take the planet’s most popular sport,
football or soccer. The rules and
gameplay are relatively simple, but the strategy is extremely complex. Depending on who’s on the field and
their particular skills, the coaches must choose between many
different formations and tactics. And no matter how talented a player
may be, they’ll only perform their best if they have a solid understanding of
football strategy such as being able to identify the precise moment to shoot or
want to pass instead. The game of chess is
also all about strategy. Each piece has a distinctive way of moving
such as a rook shifting horizontally or vertically across the board,
a knight jumping over other pieces or the powerful queen going pretty
much anywhere she wants. Mathematicians have actually proven
that there are more potential chess game variations than
atoms in the universe. And with so many possible outcomes, having a clear strategy is absolutely
essential to creating a winning game plan. Well, creating a winning strategy
is also a big part of BI. You may recall learning
about data strategy, which is the management of the people,
processes, and tools using data analysis. Similarly, business intelligence strategy
is the management of the people, processes, and tools used in
the business intelligence process. As you’re discovering, BI is complex and it requires a 360 degree
view of the organization. Thoughtful preparation to
effective strategy is a must. In this video,
we’ll explore how that works. Let’s start with people. The most important thing here is to
make sure people are working together in a positive way. Sometimes several departments
in the company are using BI, but the processes are siloed, meaning they
lack communication and collaboration. Maybe the sales team doesn’t have
access to important marketing data or human resources is tracking valuable
employee data, but only for their own internal purposes. So the first thing to do is simply
communicate with all of the team members and stakeholders who are involved. Include people from all
levels of the organization so you get many diverse perspectives. Begin by asking them some key questions
such as, are our BI teams and professionals coordinated? Is there any overlap
among their functions? Who should be responsible for
establishing the rules and policies that govern BI processes? Note that BI governance involves
defining and implementing BI systems and frameworks within an organization. This is different from the concept of data
governance which you may know is a process for ensuring the formal management
of a company’s data assets. Now most importantly in the people step,
be sure to ask about the vision for the BI process. And how does that vision align
with current business strategy? A vision specifies your desired outcomes
such as winning the football game or chess match. The second element of
BI strategy is process. By now, you’ve established who will
be responsible for the rules and policies that govern BI processes. So some questions to ask
these people include, what solutions are we using and how? Which of them bring value? What types of solutions
do we plan to implement? How will we deliver them? How will we support them? In addition, having a user support framework is
a critical part of the process. So be sure to dedicate enough
time in training and education, a feedback system, and ensuring users
are getting value from the tools. Which brings us to the tools
part of the BI strategy. One of the most important concepts to
note here is to choose each tool with the user in mind. Consider which dashboards, reports and
other solutions will be most effective. Ask, do different users, teams and
departments require different technologies? Which technologies
do we have access to? Can we gain access to others if needed? How will we measure success? Here you want to establish key
performance indicators or KPIs for each particular business need. Soon you’ll learn a lot
more about KPIs and explore how organizations use them
to achieve objectives every day. But for now, just understand that
a KPI is a quantifiable value, closely linked to business strategy, which
is used to track progress towards a goal. In other words, KPIs direct you towards
achieving your desired results. But in order for KPIs to do their job,
it’s important that the tools you select align with the KPIs established for
each particular project. The last step in this process is
documenting everything you’ve learned. Many BI professionals use specific
BI documents to note stakeholder requirements, project requirements,
and strategy. These are essential tools that can
really help you capture the big picture, stay organized, and
make an impact at your organization. You’ll learn exactly how to create
these documents in an upcoming reading. As a final point, keep in mind that your
particular level of involvement in BI strategy will vary depending on the size
and structure of your business and team. But having a broad understanding
of all the elements involved is a valuable asset for
any BI professional.

1. Understand the business intelligence landscape. Before you can contribute to a BI strategy, you need to understand the BI landscape. This includes understanding the different types of BI tools and technologies, as well as the different ways that BI can be used to improve business decision-making.
2. Identify the business needs. Once you understand the BI landscape, you need to identify the business needs that BI can address. This includes understanding the organization’s goals, objectives, and challenges. It also includes understanding the data that is available and how it is used.
3. Develop a BI strategy. Once you have identified the business needs, you need to develop a BI strategy. This includes defining the BI goals, objectives, and scope. It also includes identifying the BI tools and technologies that will be used, as well as the BI team that will be responsible for implementing and maintaining the BI solution.
4. Implement the BI solution. Once you have developed a BI strategy, you need to implement the BI solution. This includes selecting and configuring the BI tools, loading the data, and creating the BI reports and dashboards.
5. Train the users. Once the BI solution is implemented, you need to train the users. This includes teaching them how to use the BI tools and how to interpret the BI reports and dashboards.
6. Monitor and evaluate the BI solution. Once the users are trained, you need to monitor and evaluate the BI solution. This includes tracking the usage of the BI tools and the effectiveness of the BI reports and dashboards.

By following these steps, you can contribute to a winning BI strategy that helps the organization achieve its goals.

Here are some additional tips for contributing to a winning BI strategy:

• Be a business partner. BI is most effective when it is used as a tool to help businesses make better decisions. As a BI contributor, you need to be able to understand the business needs and translate them into BI requirements.
• Be a data expert. BI is all about data. As a BI contributor, you need to have a strong understanding of data analysis and visualization techniques.
• Be a technology expert. BI tools and technologies are constantly evolving. As a BI contributor, you need to stay up-to-date on the latest trends and technologies.
• Be a communicator. BI is all about communicating insights to decision-makers. As a BI contributor, you need to be able to communicate complex ideas in a clear and concise way.

Business intelligence may seem like a new
concept, but it’s actually been around for centuries. All throughout history business leaders
from around the world have used BI to set the bar for best practices. In fact, the term business
intelligence dates back to 1865, when it appeared in the encyclopedia
of commercial and business anecdotes. The book used the term to recount
how a banker, Sir Henry Furnace, had great business success
by collecting data and quickly acting on information
before his competitors could. It described Furnace as
having created a complete and perfect train of business intelligence. Well all aboard, because in this video
we’re going to get your BI train moving. And just like any train trip, this one
starts with mapping out where you are and where you want to go. In BI,
mapping a route requires a data model, which is the first tool in your toolbox. Data models organize data elements and
how they relate to one another. They help keep data
consistent across systems and explain to users how
the data is organized. This gives BI professionals clear
directions when navigating a database. All right,
the second stop on our train ride, and the second tool in your
toolbox, is the data pipeline. A data pipeline is a series of processes
that transports data from different sources to their final destination for
storage and analysis. Think of the data pipeline as train
tracks, spanning, passing, and crossing over vast distances. Data is transported along these channels
in a smooth automated flow from original sources to target destination. But that’s not all. Along the way,
it’s up to BI professionals to transform that data so that by
the time it pulls into the station or database, it’s ready to be put into use. One example of this is ETL, or
extract, transform, and load. As a refresher, ETL is a type of data
pipeline that enables data to be gathered from source systems,
converted into a useful format, and brought into a data warehouse or
other unified destination system. The process of ETL plays a key role
in data integration because it enables BI professionals to take
data from multiple sources, consolidate it, and
get all that data working together. Okay, now we’ve come to our third tool,
data visualizations. You likely know that data visualization
is the graphical representation of data. Some popular data viz
applications are Tableau and Looker. These apps make it possible to create
visuals that are easy to understand and tell a compelling story. This way people who don’t have a lot of
experience with data can easily access and interpret the information they need. Think of data visualizations as
the photos you share with friends and family after your train trip. The best ones are clear, memorable, and
highlight the specific places you went, the important sites you visited and
the interesting experiences you had. BI professionals use data
visualizations within dashboards. Our final stop on the ride. As you may know, a dashboard is
an interactive visualization tool that monitors live incoming data.
Picture the dashboards used by train drivers.
They pay close attention to these tools in order to constantly
observe the status of the train engine and
other important equipment. Dashboards keep the drivers connected
with the control center to ensure that routes are clear and
signals are functioning properly. And the drivers can quickly scan
the dashboard to identify any hazards or delays that might affect train speed or
schedule. No matter which BI tool you’re using, a very important concept
in our field is iteration. Just as the railway workers are constantly
evaluating and upgrading trains, tracks, and other systems, BI professionals
always want to find new solutions and innovative ways to advance our processes. We do this through iteration. Iteration involves
repeating a procedure over and over again, in order to keep getting
closer to the desired result. It’s like a railway engineer repeatedly
testing out signaling systems in order to refine and improve them
to ensure the safest possible environment for railway travelers.
In upcoming courses, you’ll learn
a lot more about iteration, and you’ll go much more in depth
with all these exciting tools. You’ll also explore all the ways
you can transfer your skills and experience with one tool and
apply them to another. Thanks so much for
joining me on this journey, we’ve got many more thrilling
destinations coming up.

• Data models are the foundation of BI. They organize data elements and how they relate to one another. This makes it easier to understand and analyze the data.
• Data pipelines are used to transport data from different sources to a central location for storage and analysis. This can be a complex process, as data may need to be cleaned, transformed, and aggregated before it can be used.
• Data visualizations are used to present data in a way that is easy to understand and interpret. This can be done through charts, graphs, tables, and other visual representations.
• Dashboards are interactive visualizations that provide a single view of important metrics and KPIs. This allows users to monitor performance and identify trends in real time.
• Business intelligence tools are software applications that are used to collect, analyze, and visualize data. There are a wide variety of BI tools available, each with its own strengths and weaknesses.

In addition to these tools, business intelligence professionals also need to have a strong understanding of data analysis techniques, such as statistical analysis and machine learning. They also need to be able to communicate the results of their analysis to decision-makers in a clear and concise way.

The business intelligence professional’s toolbox is constantly evolving as new technologies and techniques are developed. However, the core tools and concepts described above will remain essential for BI professionals for years to come.

Here are some additional tips for using the business intelligence professional’s toolbox:

• Choose the right tools for the job. Not all BI tools are created equal. Some are better suited for certain tasks than others.
• Integrate the tools together. BI tools can be used together to create a complete solution. This can help to improve efficiency and productivity.
• Automate the process. BI tools can be used to automate the data collection, analysis, and visualization process. This can save time and resources.
• Monitor and evaluate the results. It is important to monitor the results of BI projects to ensure that they are meeting the desired goals.

By following these tips, business intelligence professionals can use the tools in their toolbox to collect, analyze, and visualize data in a way that helps businesses make better decisions.

In business intelligence, what does ETL stand for? 

Extract, transform, and load

ETL stands for extract, transform, and load. ETL is a type of data pipeline that enables data to be gathered from source systems, converted into a useful format, and brought into a data warehouse or other unified destination system.

You have almost reached the end of this first section of the Google
Business Intelligence Certificate. So far, you’ve been introduced to
the exciting world of BI, learned about lots of potential careers, and discovered the valuable contributions
that BI professionals make every day. You have also gained some key
foundational knowledge about BI strategy, as well as data maturity. And how BI processes and tools enable organizations to
advance to higher maturity levels. We’ve covered a lot and I’m sure you
have so much to think about already, but that’s a great thing. It means you’ve gathered data,
are considering all you’ve learned, and are beginning to monitor
your own progress. That’s what intelligence is all about. As this course continues, you’ll keep
building on a strong base you’ve created. Soon you’ll also discover how to tap into
our diverse community of learners just like you in order to get the support you need
along the way. As I noted earlier, collaborating with others is a really
great way to tackle challenges, brainstorm solutions, and pool resources, just like the team members who
partner with the BI professionals. The community, you can access through
discussion forums is an invaluable resource for
you as you progress on your BI journey. In the discussion forums,
learners explore BI tools and techniques, help each other troubleshoot,
offer support, and so much more.
They share their career goals and which field they hope
to apply their BI skills. It’s a great place to just meet and network with other people who
are also interested in BI. I hope you’ll take some time
to engage with other learners. It will make your experience
more fulfilling and fun. Congrats again on all the progress
you’ve made thus far. Awesome job.

[MUSIC] My name is Gagan. I am the director of data and
analytics team in finance. My teams focus on data BI, reporting and
visualization solutions for our partners. Our job is to make data more useful so people can make good business
decisions using that data. So when I started my career,
I started in software development and there were no data teams at the time. There were no dedicated data
science functions at the time. If you asked my prior
version from 20 years ago and imagine that where I would be, I would
have never imagined I’d be here at Google. I would have never imagined I’d
be doing this as a full-time job. There were multiple individuals who are
really good at a lot of different aspects of what makes a really good BI person. If I’m working on a problem,
I talk to people. I figured out over the course of time
working with different individuals for example, I talked to one of my managers. She was really good at coding. Her SQL code and how she wrote it and
how well organized it was, I learned so much from her. I also worked with another
individual in my career who was really good at organizing and
understanding how to design metrics. I met with another person who was really
good at telling stories through data. So I had this opportunity
of informal networking and working with these individuals
who I really admired for what they brought to the table and
learning from them. Over the course of time, there are a lot of networking
opportunities that have arisen. There are lots of LinkedIn groups. There are a lot of professional networks
perhaps where you’re working perhaps outside. There are local chapters of BI data
science analytics that you could be a part of. So I have over the course of time,
the resources have changed and the resources that I’ve
utilized have also changed. But I would say the early for
many years of my BI experience, data analytics experience, those
individuals that I was able to understand and the specific skills that they
brought to the table was very useful. Networking is not about reaching to
somebody who’s more experienced or more senior than you. It’s building and understanding how
to reach out to the right people, how to make those connections. If you actually take the word networking
out and say “What am I trying to do?” It’s actually building good
professional relationships. And like any relationship,
it’s a two way street. What can you offer in that partnership? You might think you don’t have
anything to contribute and you are only trying to
learn from the individual. They definitely might have
more technical expertise or the experience behind them, but
they do not have the life experiences, the domain expertise from
where you’re coming from. And they might value understanding
where you’re coming from and how you’re trying to grow as well.

As you know, you’ll complete a graded assessment at the end
of each section in the course. And now’s the time to prepare
for your first one. This assessment will be
an effective way to verify your understanding of key
business intelligence concepts. It will also help you build confidence in your
understanding of BI while identifying any areas where you can
continue to improve. Assessments can sometimes
feel overwhelming, but approaching them
with a strategy makes them much more manageable. Here’s a list of
tips you can use to set yourself up for success. Before taking an assessment,
review your notes, the videos, readings, and most recent glossary to refresh
yourself on the content. During the assessment,
take your time. Review the whole test before
filling in any answers. Then answer the easy questions. Skip the ones you don’t know
the answer to right away. For multiple-choice
questions, focus on eliminating the
wrong answers first. Also, it’s a good idea to
read each question twice. There are often clues that you
might miss the first time. If you start to feel anxious, calm yourself with
some mental exercises. One way to do that
is by completing a simple math problem in your head or spelling
your name backwards. This also helps you recall
information more easily. Before you submit
the assessment, check your work,
but be confident. Sometimes people change an
answer because it feels wrong, but it’s actually correct. Your first instinct is
usually the best one. Finally, trust yourself. Often people know a lot more than they give
themselves credit for. Everyone learns at different speeds and in different ways. But it’s important to
maintain your momentum. Take the time you need
and when you feel ready, keep going ahead.
You’ve got this.

1. Prepare for the quiz.

The best way to do well on a quiz is to be prepared. This means reviewing the material that will be covered on the quiz, taking practice quizzes, and getting help from your instructor or a tutor if you are struggling with any concepts.

2. Manage your time wisely.

It is important to pace yourself during the quiz so that you have enough time to answer all of the questions. Don’t spend too much time on any one question, and if you get stuck, skip it and come back to it later.

3. Read the questions carefully.

Make sure you understand what each question is asking before you answer it. Don’t just read the question quickly and start writing down your answer. Take the time to read it carefully and make sure you understand all of the terms and concepts.

4. Eliminate the wrong answers.

If you are not sure of the answer to a question, try to eliminate the wrong answers first. This will help you narrow down the possible answers and make it easier to choose the correct one.

5. Trust your gut instinct.

If you have two answers that you are unsure of, go with your gut instinct. More often than not, your first instinct is the correct one.

6. Don’t change your answers unless you are sure you made a mistake.

It is tempting to change your answers if you start to second guess yourself, but it is usually best to stick with your first choice. Changing your answers can actually make your score worse.

7. Take a deep breath and relax.

It is normal to feel a little bit nervous before a quiz, but try to relax and stay calm. Taking a few deep breaths can help to clear your head and focus on the task at hand.

8. Check your work.

Before you submit your quiz, take a few minutes to check your work. This will help to catch any careless mistakes.

By following these tips, you can improve your chances of doing well on your next quiz.

Here are some additional tips that may be helpful:

• Get a good night’s sleep before the quiz.
• Eat a healthy breakfast on the day of the quiz.
• Arrive at the quiz early so that you have time to relax and settle in.
• Bring a watch or other timer so that you can keep track of your time.
• If you have a disability that affects your ability to take quizzes, let your instructor know in advance so that they can make accommodations for you.