While data analytics is a term that includes various techniques and methods of processing raw data to get conclusions about certain information or issues.

So that big data analytics can be interpreted as a method and process of processing big data to produce certain insights such as market trends, customer preferences, and other unstructured data as input for the company.

Big data analytics covers the entire process of collecting, structuring, and analyzing data from various corporate data sources.

Types of Big Data Analytics

The types of big data analytic are more or less the same as the types of data analytics in general, namely:

Descriptive Analytics

This type provides a summary of previous data in an easy-to-read form. Descriptive analytics contains an explanation of what has happened over a certain period of time, for example reports on profit, sales, revenue, etc.

Diagnostic Analytics

This type focuses on analyzing why something happened. Diagnostic analytics takes more diverse input data to find facts than and make hypotheses. Here, data recovery, data mining, and tracing are carried out.

Predictive Analytics

Predictive analytics is a type of data processing to predict possibilities that will occur in the near future, such as predictions of customer trends and market trends.

Prescriptive Analytics

Prescriptive analytics combines information obtained from previous analyzes to provide suggestions or determine the next course of action. The process utilizes machine learning and artificial intelligence technologies.

Benefits of Big Data Analytics

Big data analytics provides many benefits for companies, especially in finding new opportunities which of course will also increase profits. Apart from that, there are also other benefits such as:

Increase Productivity and Efficiency

Big data analytics can collect and process large amounts of data so that more input is obtained which can increase work productivity, both product improvement and development (upgrade).

Big data analytics can also work automatically with the use of AI and machine learning so that it can reduce the risk of data processing errors.

Speeding Up Decision Making

With the use of technology, large amounts of data can be processed quickly, including when there is a new data source. This allows the root or core of the problem to be found quickly, so that decision making for the next step will be more efficient.

Knowing Market Conditions

Big data analytics includes analysis of market or market data along with current trends. With these inputs, the company can produce products that can compete and compete even better than its competitors in the market, because customer personalization has been carried out.

Improve Customer Experience

Big data analytics is able to improve the user experience by analyzing the digital footprints left by customers to reveal a lot about their behavior, needs and what they like or don't like. Thus, the company can update its products to meet these needs.

Reduce Cost

Big data analytics uses advanced technologies such as the cloud, which has unlimited storage, to store its data, thereby reducing the cost of using multiple storage devices.

In addition, using tools such as Hadoop and Spark can identify more efficient and cost-effective ways of doing business. AI and machine learning can also predict the costs involved.

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