Data Analytics and data Analysis are frequently treated as identical terms. However, in real, these terms have slightly different significance. Data analysis is a broad term and denotes to the process of analysing and compiling the big data into meaningful information and presenting the findings to help the management to make decisions. A data analyst uses data analytic tools and techniques to perform data analysis. Data analytics is a sub-component of analysis process and involves using techniques and tools.
Data Analysis is a process of cleaning, investigating, training and transforming the data to extract valuable information and conclusions that will help in making precise decisions for a business. Tools used in Data Analysis are Tableau public, Google Fusion Tables, Open Refine and many more.
Analytics involves machine learning, utilizing data, and statistical analysis along with computer based models to generate better insights and get better decision making. It is a process of transforming the data into actions with insights and analysis for problem solving and decision-making. Tools used in the Analytics include SAS, Microsoft Excel, Python, Apache Spark, Tableau and other important tools.
Here is how the Data Analysis is important for an organization:
Some of the benefits of Data Analytics are: