<BIG DATA>

What is Big DATA?

A massive amount of data which is difficult to manage / analyze because of its volume and complexity is BIG DATA. Big data comes in all sizes, all forms from various sources.

Structured + semi-Structured + Unstructured Data --> Big DATA

"If water in a glass is considered as a data, then the raging river would be the Big data."

I am having 1 TB worth of data, does it come under Big Data?

If your data is not organized, if it is difficult/impossible for sorting manually. Yes it is Big Data. So, "Big Data" is not primarily about the data size, it is about the data quality.

BIG DATA <==> BAD DATA

The minimum size for a data to be promoted to become Big Data is 1 GB

Characteristics of Big Data:

• Volume
• Value
• Veracity
• Visualization
• Variety
• Velocity
• Viscosity
• Virality

Why Big DATA?

To uncover hidden patterns, market trends, unknown correlations, to gain competitive advantage and to make informed business decisions. It's important for organizations to analyze and get insights to improve efficiency of current processes and empower new business models.

Data Science --> Big Data ...?

One of the reasons why data science is at its peak now is because it processes a huge amount of structured, semi-structured, and unstructured data to extract insight meaning, from which one pattern can be designed that will be useful to take a decision for grabbing the new business opportunity, the betterment of product/service, and ultimately business growth.

How Big Data + Data Science helps for betterment?

• Objective / the issue of business
• Collection of relevant data, from the past till date
• Cleaning and filtering collected data
• Explore the filtered, cleaned data
• Creating a model by analyzing data
• Visualization of finding by interpreting data or creating a model for a businessperson.
• Help businesspeople in making the decision and taking the step for the sack of business growth.

Once you can visualize your decades old data in a form that you can be able to see clearly on what went wrong/right, how to make it better/best and to grow/accelerate to next level.

Data generation is currently skyrocketing. According to the latest estimates, 328.77 million terabytes of data are created each day. 2023 Daily Data

Sources of Big Data:

• Sensor Data from devices
• Transactional Data such as vouchers, invoices, receipts
• Data from Social media platforms
• E-commerce transactions
• Medical records
• E-Mails that we send and receive
• Internet Clickstream Logs.

How to process Big Data?

Ok now you say Big Data has some unbelievable scope for an organization, now say me how can I process it.

Well, here you go,

• Apache Hadoop
• NoSQL Databases
• Spark

These are the tools and Technlogies which allows you to process the Big Data, anyhow you need to understand the flow to play with Big Data, which is,

Collect --> Process --> Clean -->Visualize & Analyze

Then, why wait? Try to understand the need for your organization and if this practice helps, well you know what you need to do :)

Watch out this space for more details on Data Science.

Thanks for reading till this.

Knowledge which is not shared is useless! I'm Aswin RAM , meet you in my next post. Keep learning, Keep sharing, Bubye!

Authors: Selvi S | Aswin RAM