What is
Data Analytics?
Data analytics is the process of looking at raw data in
the hopes of finding the patterns or trends which could be used to create
useful data in order to draw conclusions and make a well-informed decision.
The rise of an information-driven society has led to data analytics becoming an increasingly popular area of research. Every discussion nowadays involves how much information is available for a particular subject. Being able to access analyzed information and data in real-time has become an integral part of our lives but also determines the way society operates in general. Data analytics are everything that we see around us. If the traffic light turns red and goes through a green signal, it is the outcome of a data analytics process. Presenting figures on the number of people who were vaccinated for Covid-19 is a data analysis process. The number of people who have been killed by Mass shootings shifts in demographics and patterns of voting, as well as the amount of time that is spent using social network sites, all of these are the results of an analysis process. Data analytics is usually presented as a complex procedure that involves figures, statistics, diagrams, graphs, and diagrams; however, the reality is that it is the same simplicity as the color red to indicate danger or green for security. If data analytics are, in some instances, a complicated process and at other times a simple analysis, who is qualified to be termed an analyst of data?
Who is
a Data Analyst?
Technically speaking, any intelligent living thing could
be classified as an analyst in data when it is able to analyze the raw data,
recognize patterns and patterns, and then use the data to create useful data
that can be used to draw conclusions and make educated choices. Humans are
naturally born data analysts. When a newborn baby is born, and it opens its
eyes for the first time motion of the eyes is notably different from adults.
This is due to the fact that infants are picking up lots of raw information,
analyzing patterns in it, and then using it to generate useful information and
take action on it. The more information the baby accumulates, it utilizes to
make a pattern of what the food source security, comfort, and protection
appears and is able to determine the mother.
In accordance with the standard definitions, any person
who is able to analyze data may be classified as a data analyst. To be able to
be classified as an analyst, there are certain prerequisites that must be
fulfilled. Basketball and football are played by anybody in public spaces.
However, those who play on the streets are not classified as footballers or
basketball players in the event that they are playing those sports in
accordance with widely accepted standards, policies, clothing equipment, and
location. To be able to call yourself a data analyst, you must meet the
required qualifications, employ the right techniques and methods for data
analysis and then present the data in accordance with the established
guidelines for data analysis. Data analytics covers a broad subject of study.
Over the course of a 24-hour day, people consume various kinds of information
and data. This means that various types of analytics based on data are
necessary to help us navigate through our lives.
Types
of Data Analytics
There are generally four types and stages of data analytics.
·
- Descriptive Analytics
·
- Diagnostic Analytics
·
- Predictive Analytics
·
- Prescriptive Analytics
Descriptive
Analytics
This
is the kind of data analytics that requires the creation of information using
historical data. It uses events from the past to find certain patterns in the
raw data. It then utilizes the patterns to generate an image of the useful
data. It is similar to recognizing your roommate within a crowd of people. If
you glance at your roommate's name, your experiences and previous events can
assist you in visualizing your friend from the crowd of strangers. Based on the
information you have that you have gathered, you invite your roommate to join
you on your drinking excursion.
This
is typically the first step and the most basic type of data analytics. It also
creates the foundation for the other kinds of analytics that can be applied
later on. Descriptive analytics is represented visually through chart charts
such as pie graphs, bars, charts, table graphs, or line graphs. They show the
events that have occurred. In the business world, these events could be the
number of sales per week or the amount of revenue that was made in the first
quarter. Social media sites could include the number of people who comment,
share, or share on a specific post or video.
Diagnostic
Analytics
Diagnostic
analytics is a specialized type of data analytics that relies on the data that
has been obtained following a descriptive analysis completed. Diagnostic
analytics attempts to clarify the reason for an event. After a night out, along
with your roommate, discover that your friend vomited throughout the apartment
in the morning. By using diagnostic analysis, you will determine the connection
between both events in a way that concludes it was the alcohol consumption that
caused the early morning vomiting.
This is generally the next stage of analytics and depends on the data that is generated in the descriptive analysis phase. Diagnostic analysis is the process of providing information about the reason the reasons for an event. This process involves analyzing the details and identifying patterns as well as relationships. An effective tool in this stage is correlation analysis, which seeks to discover connections that are present in the data or data. The company's sales growth could be linked to lower prices in the same time period. A popular television show could be linked to an increase in the number of new subscribers signing up to streaming services. If a mass shooting takes place in the media, they will employ analysis of diagnostics to understand the motives of the shooter. If the number of cases of covid-19 is declining, does this suggest that the vaccines are working? Do you see a connection between the two? Diagnostic analytics seeks to answer these questions. It is actually a mix of diagnostic and descriptive analytics.
Prescriptive
Analytics
The Prescriptive Analytics stage is the third step in data analytics. This stage defines what needs to take place with data and data gathered during the initial three phases of data analytics. The accuracy of data produced at this point depends on the accuracy and the quality of the data gathered during the previous stages.
If you've correctly identified that each time you go for a drink with your roommate, you vomit all over your flat the next day. The last step is to decide how you will take into account that data. Do you intend to end your drinks along with your partner? Are you planning to counsel your roommate to cut down on the number of glasses consumed? Do you think the drinking habit is worth it? Do you think the constant smell of vomit in the bathroom is acceptable? This is the point at which you make use of all the information that you have gathered from the earlier phases of analysis to make an informed choice.
This stage
is the most advanced, involving analyzing graphs, performing experiments, and
machine learning. It is by far the most important component of data analytics
as the data generated is crucial to making decisions, formulating policies, as
well as the creation of goals and creating goals. Suppose the government
decides to institute lockdowns in order to limit transmission of the virus. The
decision is made during this phase of analysis. If a streaming service decides
to end a TV show, it is at this point that the decisions are taken.
The
World of Data Analytics
Data analytics is not as difficult as most people
believe. It's a commonplace behavior that we all engage in without even
realizing it. The instruments we choose to employ are the intricacies of data
analytics. You're doing a data analytics procedure if you detect dark clouds
and correctly anticipate a major storm. Data analytics is also used when a
meteorologist utilizes satellites to properly anticipate a severe storm. Data
analytics is the act of condensing large volumes of data and presenting it in a
meaningful and understandable manner. It helps us understand the world we live
in by simplifying the facts and information we see around us.
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