Most people in the tech world are gung-ho about the virtues of Big Data analytics. Don’t we always keep hearing these stories about how Big Data analytics are hugely helpful to the companies? Not only it doubles up customer retention, but also increases cross-sell to a great extent, and allows the companies to cut costs by 95%.

In fact, business leaders are just so fervent about its potential of transforming a business that in some spheres, it is also being regarded as “the planet’s new natural resource.”
Despite the fact that most people keep promoting a specific tool or solution, what remains crucial to succeed with Big Data is solving business problems. So, here, let’s begin by understanding Big Data.

So what makes Big Data different?

Well, to start with, Big Data can be anything. Like it refers to a technology set or solution architecture, and often it is even used for describing a business challenge. Many a time it is also used to refer to the data and this way the term keeps evolving.

Here are the few definitions that help understand Big Data better

• Big Data is a collection of Data requiring new forms of processing as it is helpful in enabling enhanced decision making, extracting new insight or new discovery.
• Data sets those are proficient in terms of high volume, high velocity, and miscellaneous data structures.
• It is a Data that cannot be processed with the use of standard databases because it is too big, too fast moving or too complex for traditional data processing tools.
• Big Data works wonders in the growth of data and how to curate, manage, and process the data within performance goals.

How to make the right move to make the most out of my Big Data?

Firstly, understand the fact that Big Data is a problem and data challenge, and not a technical issue. This way for most organizations out there the amount of data and processing power is not really a challenge.

Some institutions such as Facebook, Google may face real technical challenges with the amount of data generated and analyzed. However, most businesses don’t have such issues.
For them, what comes around like a real challenge is to define the problems that you want to solve with data and ensure that the data is available to help you in solving them. The problem is going to drive the solution regarding which tools and technical solutions work best for your organization.

What are the kinds of problems that Big Data can efficiently solve?

It starts with a business challenge, product or idea. It varies from price optimization, predicting technical issues before they occur, personalizing customer communication for a product, keeping the business safe, managing risk, reducing the cost of fuel, or it can be anything.
Thus, there can be a million problems faced by a cross-functional team in any business that Big Data can efficiently solve.

Next, you need to prioritize a few issues that can deliver a clear return on investment in the short to mid-term with somewhat limited effort. You can start off by solving a couple of different types of problems as that ensures that the solution is flexible and scalable, instead of supporting just a single use case.

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Which Big Data Solution is Best for your business?

It should be ensured that the problems are clearly defined and tested with end-users or internal stakeholders before you start working on the solutions. As soon as the problem is well understood, it is time to focus on the solutions, as mostly there are a lot of them.
Here we haven’t yet mentioned unstructured vs. structured data, data lakes, NoSQL, MPP databases, Hadoop, BI tools such as IBI, MicroStrategy, Microsoft BI or SAP HANA. It’s because there is no generic optimal solution for big data problems or organizations. Thus, what should drive the solution and selection of tools is the business problems and requirements.

Which Big Data solution to select?

Before you implement tools, write a single line or code or data query, you can opt to prototype, test, and model the solutions. Once you have successfully proven that it works, you can start with the specification and planning of the technical implementation. This not only saves time and money, but also helps in delivering better results.

Final Note:

Out there you will find numerous of great Big Data Technology experts who help organizations in solving business problems and create new products and services with the help of data. Their methodology enables you to test problems and solutions without investing in expensive technology, and ultimately work their best to deliver great customer success.