Data analytics is a process of investigating sensitive or raw data to reach certain conclusions. Performance can be optimized by using Data Analytics.
Data driven by Analysis is known as DATA ANALYSIS.
Well when you need to conclude any data which is raw at that moment Data Analytics is used rather it can be said that after analyzing raw data to draw trends and reach it’s conclusions.
“Data is growing approximately 60% per year.”
Data Analytics makes all the sensitive and raw data meaningful.
Technology | Uses in Data Analytics |
---|---|
Microsoft Excel | Helps in creating reports and mathematical functions. |
SQL | Used to interact with the data stored in Database. |
Python | Python helps in creating and managing data structures quickly. |
Tableau | Tableau allows you to prepare, analyze, collaborate and share your insights. |
SAS | SAS performs functions like retrieve, report and analyze the statistical data. |
R Programming | Helps in building practical model and identifies patterns. |
Microsoft Power BI | Power BI supplies interactive data visualization. |
Microsoft PowerPoint | Helps in representing data. |
Microsoft SQL Server | Adds value to already present data in the database. |
Oracle | Doesn’t compromise in security also provides capabilities to address the entire analytical process. |
If raw data is not analyzed that data is fully wasted so data analytics is very necessary.
Performance of any business can be optimized using Data Analytics. With it the costs of business model can be reduced
a firm can also use data analytics for decision making which helps satisfying the customers and leads to better goods and services.
Helps in improving the managerial operations of organization to the next level.
Visualization is one of the most important step which helps to get pictorial representation in the form of various graphs, pivot tables etc.
Q.1 Is Data Analytics having any relation with statistics?
A. Maybe
B. Absolutely
C. Not at all
Q. 2 You are having a lot of raw data so what will be your first step?
A. Arranging Data
B. Defining Conclusion of Data
C. Discussion with the Group
Q. 3 Which of the following Technology is used for Analyzing Data?
A. HTML
B. Python
C. Object Oriented Programming
NOTE: Find out the answers in the above paragraphs.
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