Data Analytics and It’s Types

In this current evolving world and with our ever-growing speed of digitalisation, we are generating more and more data. And with the advancements in techniques and hardware, we can also store this vast amount of data. The world has a shift where the internet not only gives data or information to us. Instead, we also generate massive data on social media websites. Ideally, companies need to use all their generated data to derive value and make impactful business decisions. Data analytics is used to drive this purpose.

Formally Data Analytics can be derived as “a discipline focused on extracting insights from data, including the analysis, collection, organisation, and storage of data and the tools and techniques used to do so”. Data Analytics uses various disciplines like computer programming, mathematics, and statistics to extract information from the data.

Major Types of Data Analytics are:

1. Descriptive Analytics: This essentially answers ‘what has happened till now? ‘For example, use historical data to generate trends like sales of a particular product by year or year.
2. Diagnostic Analytics: This type of analytics is done to answer, ‘why has it happened?’ For example – If we want to analyse and determine the factors that contributed to the sales of that product. This can be achieved using diagnostic analytics.
3. Predictive Analytics: It essentially tells us ‘What will happen in the future?’ For example, if we can forecast how the product’s sales will be in coming years.
4. Prescriptive analytics is used to answer, ‘What do we need to do?’ Prescriptive analytics uses machine learning, business rules, and algorithms in business. For example – If we want to prescribe what steps we need to take to improve the sales for the coming year.
5. Cognitive Analytics is an intelligent technology that covers multiple analytical techniques to analyse large data sets and give structure to unstructured data.

Major Advantages or business outcomes that can be achieved using different kinds of analytics can be summarised as follows –

• Data-driven Decision Making
• Enhance Customer Experience
• Optimised operations
• Targeted Marketing
• Actionable insights

Leveraging Data Analytics can greatly boost an organisation’s efficiency and is a trend that is being incorporated by all major players at a rapid pace.

~ Nishkam Shivam, Data scientist @ Bristlecone | Ex- Walmart | Ex- Accenture

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