Raw Data and You, Choose what are you fit for Data Analytics / Business Analytics
Raw data is what you get abundantly. Every business and person who runs that business, works with analytics from data collection to report generation process as part of business intelligence. It is always a trouble to work with things which are in their crude form. As the technology eased up many things in life to help us in analysing smallest things to analysing extremely abundant data. IBM said, every day we create 2.5 quintillion bytes of data or more. As this data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data. Every kind of business has its relevant data here. So you need to dig for your relevant data using Data Mining processes and then comes the Data Analytics part.
The scope, purpose and focus of the Data Analytics and Data Mining differ from each other.
Here we talk about Data Analytics. This is the process which helps businesses to analyse things to make better business decisions or they can disprove or approve theories in science.
To put it simple we quote the line from Wikipedia:
“Analysis of data is a process of inspecting, cleaning, transforming and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making.”
There is also a confusion in the industry between the terms Data Analytics & Business Analytics. So we write a little more on this to show you the gap between them, which can help you analyse it and understand the terminology easily. As both of them are involved in collection and analysis of data, both conduct their analysis in order to provide businesses an effective decision making information.
However business analytics focuses more on processes, functions, operations and overall architecture of an enterprise. The critical and most important thing which differs BA with DA is “BA is the practice of enabling change by identifying business needs and determining solutions to those business problems.” Whereas data analytics focuses on the process of collecting, cleaning, analysing, reporting and presenting data as information. “DA is the process of breaking down the data and take necessary steps involved in converting raw and messy information into clean and usable knowledge.”
A business analyst might use information to predict future business performance using past business performance and a data analyst might compare an organisation with its competitors to identify business patterns and trends which could help take better decisions to encourage success.
Why you should consider to be a Data Scientist (Data Analyst)?
Consider yourself that you are born for this if you have these traits like being inquisitive, persistent, self-motivated and analytical by nature with an interest in helping guide strategic decisions for businesses. Also consider that you can be a Data Scientist if you have creative thought process in identifying innovative solutions with an investigative approach of analysing data.
Inquisitive & Self-motivated | Creative & Flexible | Strategic & Collaborative
“Behind Every Good Decision There is Data Analytics” - ExcelR