Data analytics: Why it is so important?

Introduction to data analytics

Data analytics is used to find meaningful insight from a set of data. Such a process is conducted with the help of certain qualitative and quantitative approaches. The basic task of big data analytics is to collect, organize, classify, transform and convert into easy to understand data along with visualization.

Today the need for data analytics is so high because every organization is data-driven and continues collecting data from a various internal and external source that may help with the organization's progress, and thus this data needs to be collected, categorized, analyzed and stored in order to derive valuable meaning out of it.

The needs for big data analytics will continue with the amount of data collected every day in the online world.

Types of data analytics

1. Descriptive analytics: With descriptive analytics, descriptions are created based on incoming data and this data is mined with the help of analytics and collected descriptions are made.

2. Predictive analytics: In predictive analytics, the data analytic makes sure that a path for the future course of action is predicted and is reliable based on the available data.

3. Prescriptive analytics: In this, the analytic suggests a course of action based on the predetermined rules and procedures so as to provide the best path that is helpful for the organization.

4. Diagnostic analytics: This type of data analytics is used to find out why a certain situation occurred. Other types of analytics help with forecasting but for this type, it helps in looking in past history to find answers.

Importance of Data Analytics

In today’s world, everything turns into data and to control and properly use such incalculable amounts of data, data analytics has a major role to play.

1. Better and quick decision making: Data analytics help in quickly collecting and analyzing new data from various sources that provide helpful information. With such a quick response, the decision makers will be able to make effective new decisions instantly and save time.

2. Improved efficiency: Since every organization is now data-driven, they collect data from both internal and external sources. The data, when processed with the help of data analytics, internally provides information about employee performance and the various courses of action that the organization can choose from. This increases the efficiency of the business.

3. Reduction in cost: Using technologies like big data analytics can save a lot of money spent on storing a large amount of data. Such analytics also help with making the most effective and efficient business decisions, which in turn help in making products that will provide the highest profit once launched in the market.

4. Better market understanding: Today, collected data is analyzed with the help of various developed algorithms that can analyze and collect a large amount of data at the same time. This process is called mining. This enables data collection from various sources and is later refined in order to get fruitful marketing plans and strategies.

5. Information about the industry: It is also capable of collecting industry-related information and can provide future market and industry scenarios. It can forecast the economy that will be beneficial for any kind of business expansion. Such industrial information will open up many opportunities for the growth of the organization and will help in building a strong brand.

6. Launching new products and services: Data analytics help in collecting information related to the customer which in turn help in understanding the customer demands and satisfaction levels. The organization can then work on launching products and services that will satisfy the target customers.
7. Identifying opportunities: With the continuously changing economy and market conditions, data analytics help in refining the stored data that help with understanding the available opportunities.