Nowadays, making the right business decision plays a key role for an organization and this decision mainly depends on one thing: data. The main objective of an organization is to produce output that has value to its customers. It's important to point out that determining the output (services, information, products, etc.) is the first step in specifying the nature, amount, regularity of the input (material, information, human resources, etc.) needed to produce it.
Objective
Data analytics analyzes the real-time and historical data of the company and using this conclusion, the company can enhance productivity and business gain. Data analytics contains a remarkable ability to identify the data which plays a key role in the benefit of the company. Data analytics help companies make the most out of the big data they have.
One of the best ways to make decisions is to examine data analytics. Since the data owned by the companies are huge, it is not eminently reliable but definitely highlights the problems and how they occurred.
Why do we need data analytics?
There is no company in today's era which is dependent on software. They need data to explore their businesses. So, as we know that there is a lot of data stored on the internet; this data can be of your day-to-day activity on the internet or can belong to any marketing field. So, for our profit, we need to analyze all data for better marketing strategies and to enhance business requirements. Suppose you are a fresher in the field of data analytics and also are running a small business and you want to earn the profit. For this, you need to understand the pattern of your customer's data, their demand, the trend in the market, and of course, your failures behind your loss. Without knowing all this, there is a chance of sinking your business. Data analytics helps in discovering new opportunities which further gives you an idea of building a better model for having smarter enterprises.
Types of analytics
- Descriptive (Business intelligence): 90% of the organizations use these analytics for condensing big data into useful nuggets of information, e.g. social analytics.
- Predictive (Forecasting): Analytics forecast what might happen in the future, probable in nature and answers the following questions:
- What will happen next?
- What is the cause?
- What if the existing trend continues?
- Prescriptive (Optimization): Advanced analytics where optimization helps in achieving the best outcomes. It results in conclusions that increase the profit of the business.
Path
An area that records a lot of data requires data analytics. Data analytics careers mainly focus on how prominent your ability is to influence the company to take a certain action. It also requires good communication skills.
Analytics tools
Data analytic tools function on the basic goal of analyzing data and extracting useful pieces from it for the betterment of the business. These tools cover the basic aspects of the market:
- Tableau
- Cloudera
- Oracle Analytics Cloud
- Microsoft Power BI
- Splunk
Future of data analytics
Data analytics is expected to drastically change the way we do business in the future. The World Economic Forum and IBM forecast that the high demand for data analytics in companies will lead to 700,000 new recruitments by 2020.
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