What is
Data Analytics? Why Data Analysis is Important?
“Drowning in data and starving for information
“Knowledge is power;
Intelligence is absolute power!”
In this article, we will discuss about data, information, the Job of a data analyst, and how a data analyst performs data analysis tasks.
We will also discuss sources of data, the Data analysis process, data analyst skills, and the Data Analytic Life cycle.
Data analyst as a career and significant certifications will be discussed in this article? I have done the “Foundations: Data, Data, Everywhere” course sponsored by Google and would like to share whatever I have learned and understand this topic.
1. What
is Data?
Originally data is plural
of “datum” a Latin word that means a single point of matter or more
formally called data points.
Data may be in the
form of raw data, useless information, unrecognized facts or in randomized
nature. When data is arranged, structured, and summarized in a recognizable
form it becomes information and information is very important for all.
2. What
is the job of a data analyst?
A Data Analyst is an expert responsible to collect data and interpret data for solving a particular problem or task.
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3. What
is Data Analytics?
Data Analytics is the
process of analyzing datasets to conclude important trends about the
information they contain. Data analytic tools and techniques enable you to
uncover patterns to extract valuable information from them.
Data helps us to
make decisions in our daily life, whether it’s about business or everyday life.
Data analysis is a technique used to analyze data to enhance business
productivity. Data is captured and gathered from different sources then cleaned, visualized and observed, analyzed to make different decisions. Now, will
go through each of the phases in detail.
4. What
are Sources of Data? Types of Data?
There are varieties of
sources for data it could be as business data, geographical data, or
business sales data. But at the heart of data-driven decision-making is data,
that is why data, data everywhere.
How data-driven
decision makes impact a business? what are the steps involved in the data
analysis phase?
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5. Why Data Analytics is Important?
Data helps us to make decisions in our daily life, whether it’s about business or everyday life. Data analysis is a technique used to analyze data to enhance business productivity. Data is captured and gathered from different sources then cleaned, visualized and observed, analyzed to make different decisions. Now We will go through each of the phases in detail.
6. Why gut instinct can be a problem?
It's essential that
data analysts focus on the data to ensure and facilitate informed decisions
making process. If you ignore data and make decision-based on your empirical
knowledge these decisions will definitely be biased and even worse which will be like gut
instinct without any data to support them leading to mistakes and wrong
directions.
The more you
understand the question or the problem to solve first and then the data related to that
particular problem, the easier it will be to uncover from data what is
required. You will then be able to locate errors and gaps in your dataset.
Ultimately you will also be able to draw and communicate your findings more
effectively. Here you may use your empirical knowledge and sense
6. Remember Simple Equation?
Data + business knowledge = mystery solved
Blending data with business knowledge will be a
common part of your process as a junior data analyst. The key is figuring out what exactly is required. Oftentimes, it depends on the goals of your
analysis. That is why analysts often ask, “How do I
define success for this project?”
In addition, ask these questions yourself to find the
balance:
·
What kind
of results are needed?
·
Who will
be informed?
·
Am I
answering the question being asked?
·
How
quickly does a decision need to be made?
For instance, if you are working on a quick or urgent project,
you may apply your knowledge and experience because you do have not enough time to
comprehensively analyze all available data.
On the other hand, but if you have enough time and resources,
then the best strategy is to be more data-driven. It is your choice as a data
analyst, to make the best possible choice.
7. Data Analysis Process.
Step1. Ask as many
questions as you can and define the problem.
Step2. Prepare data by
collecting and storing the information.
Step3. Process data by
cleaning and checking the information using data cleansing techniques.
Step2. Analyze data, and find
patterns, relationships, and trends.
Step2. Share data with
your audience and management.
Step2. Act on the data
and use the analysis results.
After going through the above process
Now check what skills
a person must have to be a data analyst.
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8. Data
Analyst Essential Skills
1. Curiosity: A
desire to know more about something, by asking the right question about a
problem. Discover earlier about new things that might happen in the near future
2. Understanding the context: Understand
what is the requirement and where the data fits into? The “Big Picture”.
3. Having a technical mindset: Technical mindset means when a data analyst deals with larger and more complex problems the first step is to break the complex problem into smaller
steps and then solve each step. This process is called a technical mindset.
4. strategy: By the word strategy we
mean being able to use the right tools, and the right approach to tackle the problem.
5. Programming and Tools. Knowledge of programming languages like Python,
database tools like Excel, and data visualization tools
Now we will discuss the data
analytic life cycle.
9. Data Analysis Life Cycle
Step 1. Plan: Decide what kind of data is needed? How data is managed? who will be responsible for this data?
Step 2. Capture Collect capture data from
different sources. Gather data from different platforms using different
techniques i.e Gumshoe research.
Step 3. Manage:
After data has been gathered next step is to manage data using the right
tools and the right approach This includes how data is stored and managed using
various sources and software tools.
Step 4. Analyze After data is gathered, and stored, it’s the
right time to create a visualization to analyze and observe data to draw effective conclusions. solve the problem, and make a decision. And support business
goals.
Step 5: Archive:
The term archive data analysis means that keep relevant data stored for
long-term use in the future.
Step 6 Destroy: Remove data from storage devices, and delete the
information shared during the process.
10. Is Data Analytics the Best Career?
Data analytics is so
important that a complete Major in Data Science has been introduced in academia.
The answer to this question is Yes, data analytics is the best career and also the
most demanding career.
11. What
Data Analytic Career Path?
You might start a career as a data analyst and with time and experience grow to analytics manager, director of analytics, etc.
12. What are Important Certifications for Data Analytics?
1. Google Data
Analytics Professional Certificate
2. Microsoft
Certified: Power BI Data Analyst Associate
3. IBM Data Analyst
Professional certificate
4. SAS Statistical
Business Analyst Professional Certificate
5. Amazon Web Services
(AWS) Certified Data Analytics
6. CompTIA Data
Analytics Plus certification
13. Conclusion
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