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The world is one big data problem.

- Andrew McAfee, co-director of the MIT Initiative

Big data is a term that describes large, hard-to-manage volumes of data – both structured and unstructured – that inundate businesses on a day-to-day basis.

Examples

Following are a few examples of big data databases, just to give y’all an idea of how big this could be:

• The New York Stock Exchange is an example of Big Data that generates about one terabyte ( 10^12 bytes ◉‿◉) of new trade data per day.

• A single Jet engine can generate 10+ terabytes of data in 30 minutes of flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.

Why is Big Data Important?

The importance of big data doesn’t simply revolve around how much data you have. The value lies in how you use it. By taking data from any source and analyzing it, you can find answers that

1. streamline resource management
2. improve operational efficiencies
3. optimize product development
4. drive new revenue and growth opportunities
5. enable smart decision making.

When you combine big data with high-performance analytics provided by Google Cloud services, you can accomplish business-related tasks such as:

• Determining root causes of failures, issues and defects in near-real time.
• Spotting anomalies faster and more accurately than the human eye.
• Improving patient outcomes by rapidly converting medical image data into insights.
• Recalculating entire risk portfolios in minutes.
• Sharpening deep learning models’ ability to accurately classify and react to changing variables.
• Detecting fraudulent behavior before it affects your organization.

How Google Cloud services helps?

Google Cloud Platform provides a bunch of different services, which cover all popular needs of data and Big Data applications.

We would be discussing two critical services i.e. BigQuery and BigTable here.