What is Big Data?
Big data is a popular term describing a large amount of structured or unstructured data that can possibly be mined for information. Although the term, big data doesn’t refers to any specific amount of data but is often used to describe an exponential growth (about petabytes and exabytes) of data.
The Three V’s of Big Data:
- Volume: Various factors contributing towards the increment in data volume. Unstructured data collected from social media, transaction based data, collected amount of sensors, people to machine interaction and machine to machine data. Previously, excessive amount of data was an issue of storage but then reducing cost of storage tends to raise of other issues like how to properly analyze the data and how to determine the relevant data.
- Velocity: Data is streaming at exceptional speed and must be managed conveniently. RFID tags/labels, GPS devices, surveillance cameras, sensors, cell phones and savvy metering are driving the need to manage deluges of data in real-time. Quick response to deal with data velocity is the challenge to most business organizations.
- Variety: Data comes in various formats structured, semi-structured and non-structured. Numeric database, unstructured text documents, audio, video, email, financial transaction based data, stock ticker data and so on. Managing, consolidating and governing such data is something many organizations are still think about.
Challenges to consider:
Most of the organizations are worried about volume of amassed data is getting to be large and it is hard to discover the most important bits of data. How to analyze it and figure out the essential data and how to use it to for best advantages are the challenges to consider for big-data.
Growing organizations are overwhelmed with a large amount of data growing day-by-day. But, what is the logic behind collecting and storing such a large amount of data if you can’t analyze it in full context or you will have to wait for so long to get results?
You may get rid of this by using big-data analytics. High power technologies such as grid computing, in-memory analytics are there to analyze the massive amount of data for you.
Why Big Data Matters:
Big data is about the rising issue/challenge that many organizations are facing as they have to deal with a large pool of data/information. It has become a crucial way for these organizations to outperform their competitors. Big data will help to create new growth opportunities, consolidate and analyze industry data which enables cost and time reduction, new opportunities, product development and optimized offerings/services, and smart business decision making.
By consolidating big data and high performance analytics, it is possible to:
- Identify root causes of failures, defects or other issues in close real-time, potentially saving billion of pennies per year.
- Streamline routes for a huge number of package delivery vehicles while they are out and about.
- Determine millions of SKUs to focus costs that boost revenue and clear stock.
- Produce retail coupons at the POS based on customer’s present and past buys.
- Send tailored suggestions to cell phones while customers are in the right zone to exploit offers.
- Recalculate whole risk portfolios in minutes.
- Rapidly identify the customers/clients who matter the most.
- Use high-powered analytical tool for information mining and to detect fraudulent behavior.