What is Data Analytics - Types of data analytics, Advantages, Applications

What is Data Analytics -

In data analytics, we are presented with the data. The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics. 

Big Data repositories have existed in many forms, often built by corporation with a special need. Organizations are capturing, storing and analyzing data that has high volume, velocity and variety and comes from a variety of a new sources, including social media, machines, log files, video, text, image RFID, and GPS.

The main goal of big data analytics is to help organization to make better business decision, future prediction, analysis large numbers of transaction that done in organization and update the form of data that organization is used. 

For Example: Big online business website like Flipkart, Snapdeal uses Facebook or Gmail data to view the customer information or behavior.

Big data analytics for manufacturing applications is marked as a 5C architecture as (connection, conversion, cyber, cognition and configration). Factory work and Cyber-physical systems may have an extended "6C system" as:

1. Cloud (computing and data on demand) -
2. Connection (sensor and networks) -
3. Customization (personalization and value) - 
4. Content / context (meaning and correlation) -
5. Cyber (model and memory) - 
6. Community (sharing and collaboration) - 

Types of Big Data Analytics -

1. Prescriptive Analytics - 

The most valueable and most underused big data analytics technique, prescriptive analytics gives you a lesar-like focus to answer a specific question. It helps to determine the best solution among a variety of choices, given the known parameters and suggests options for how to take advantage of a future opportunity or mitigate a future risk. 

Examples of prescriptive analytics for customer retention include next best offer analysis.

2. Diagnostic Analytics - 

It consists of asking the questions: why did it happen? Diagnostic analytics looks for the root cause of a problem. It is used to determine what happened. This type attempts to find and understand the causes of events and behaviours.

3. Descriptive Analytics -  

This technique is the most time-intensive and often produces the least value; however, it is useful for uncovering patterns within a certain segment of customers. Descriptive analytics provide insight into what has happened historically. Examples of descriptive anaytics include summary statistics, clustering and association rules used in market basket analysis. 

4. Predictive Analytics - 

The most commonly used technique; predictive analytics use models to forecast what might happen in specific scenarios. Example of predictive analytics include next best offers, churn risk and renewal risk analysis.

Advantage of Big Data -

Here we will discussing about the Advantages of Big Data:

• One of the biggest advantages of Big Data is predictive analysis. Big Data analytics tools can predict outcomes accurately, thereby, allowing businesses and organizations to make better decisions, while simultaneously optimizing thier operational efficiencies and reducing risks.

• By harnessing data from social media platforms using Big Data analytics tools, businesses around the world are streamlining their digital marketing strategies to enhace the the overall consumer experience. Big Data provides insight into the customer pain points and allows companies to improve upon their products and services. 

• Being accurate, Big Data combines relevant data from multiple sources to produce highly actionable insights. Almost 43% of campanies lack the necessary tools to filter out irrelevent data, which eventually costs them millions of dollars to hash out useful data from the bulk. Big Data tools can help reduce this, saving you both time and money. 

• Businesses are using Big Data analytics tools to understand how well their products/services are doing in the market and how the customers are responding to them. Thus, the can understand better where to invest their time and money.