Data analytics is a process of analyzing raw data in order to make conclusions and find trends. It is important for businesses for several reasons. Data analysis refers to data collated, checked through the establishment of the audit analysis model, re-calculation, judgment, and other operations will be the real status of the audited entity data is compared to the ideal state, which found the audit trail, gathering audit evidence Process.
In other words, Data analytics is an organizational process performed by data analysts that is far more than just presenting numbers and figures to management. It helps organizations and businesses to gain insight knowledge that they need for further production of growth. Data analysis applies generally to all processes and resources necessary for the collection and analysis of data.
Benefits of data analytics to business:
- Better Decision making: Data analytic increase your decision-making. Rather than relying on common sense alone, companies looking at data before decision making. The main benefit of big data analytics is improve decision-making significantly. When big data join forces with artificial intelligence and machine learning, companies are better equipped to make better predictions.
- Delivery of relevant products: Product is the lifeline of any company often it will make small companies to big brands. It helps to the Product management team of the company to make new innovations, improve services, and new feature. It helps the company to stay competitive inflexible and new innovation trends.
Therefore, it is a good choice to treat data analysis as a career. But, what are data analysis doing? What skills are needed?
Data analysis is not necessarily dealing with big data; it may only be small or small. Usually the expertise required for data analysis lies in ~ mathematics, statistics, or Computer science and other related degrees and backgrounds, the most common job skills requirements are SQL, R, SAS, Excel, and as the amount of data that needs to be processed is increasing, Hadoop is also listed as one of the necessary basic conditions by many companies.
Requirements for data analysts:
- Familiar with related businesses. For example, if you are a bank-related data analyst, you must be familiar with banking related businesses to be able to interpret data.
- Familiar with common analysis tools and basic analysis methods, such as R language, SQL tools, SAS and other statistical tools, as well as the analysis methods applied to these tools.
- Familiar with the procedures of data collection, sorting, and analysis. For example, you must know where the data to be analyzed comes from, whether it is taken from internal data, or needs to be captured externally.
- Familiar with platforms or tools that can handle larger amounts of data, such as Hadoop, Spark, NoSQL, etc.
So from the above, you can probably understand the work content of a data analytics companies in India, which is to first understand the relevant business, know what information the industry needs to interpret, and know the meaning of the data after interpretation. Then it is necessary to use tools to capture and process data, analyze and obtain results.
