How to avoid these 4 Big Data failures.

Since the market crisis in early 2008, the technology of big data has become very popular.

Also, it is a way of gaining insight and generating value for businesses. The process involves analyzing large data to gain value.

The process is not dependent on how large your business data is, but on how much value it adds to your business. It enables smart-decision-making, cost reduction, a new product in development and the optimization of offerings.

Further, Big data in combination with high-powered analysis give businesses an edge. As a result, business-related tasks are accomplished with ease.  These Tasks include:

  • The determination of the main causes of defects, issues, and failures in marginally real-time.
  • The recalculation of the whole risk portfolio. This occurs within minutes.
  • Early detection of fraudulent practice or behavior before it causes harm to a business.
  • The generation of coupons at the point of sale on the basis of customer’s buying habit.

Thus, if a data cannot be ingested, processed and examined in real-time to meet a particular business task or requirement, then no matter how large it is, it is useless.

What is a useful Big Data?

Today, not any data is Big Data. There are unique attributes that make a data BIG.  The attributes are the four V’s – Volume, Variety, Velocity, and Veracity.

  • Volume: This is the main nature that brings the “big” to Data. Every year, the amount of data generated in the world grows exponentially.
  • Variety: With technological development, information has become more digitized with high Variety. Structured and unstructured data types are common with Big Data. Unstructured data is the main concern in Big Data. With this type of data, there are no rules. Big data use technology to make sense of unstructured data.
  • Veracity: How trustworthy is the data? Is it representative? Can you rely on the data to make decisions? Veracity is a vital requirement for Big Data.
  • Velocity: The frequency of incoming data or generated data for processing. These data must be frequent and regular.

We recognize Value as the fifth V. Big data must be useful. The real aim of Big Data is actually to create insight and increase business productivity. Thus, usefulness is a criterion that it must meet.

Meanwhile, a lot of businesses are beginning to use Big data to make the most of their business. Even so, the use of this technology doesn’t necessarily translate to business success.

This technology is great! But when you delve into it unprepared or without seeing the whole picture, you begin to scramble. So, before you jump into this bandwagon, preparedness is very important.

We are sharing 5 of the most common errors that you must avoid as you use the technology. With the right information, you can execute it successfully. Also, you can enjoy the huge benefits this technology offers.

5 errors to avoid

We have put together some of the deadliest errors your business could make with Big Data. We have also included suggestions on how to avoid them.

ERROR #1 – Lack of Big Data roadmap

No matter how good a thing is, if there is no plan, its benefits are almost not maximized. It is an established fact that data grows exponentially.

Also, your business will keep generating data (both structured and unstructured data). Thus, the generated data makes it hard to decide how to use it (in real-time) to make good business decisions.

The Suggestion…

Instead of collecting loads of random data, develop a strategic Big Data roadmap. The roadmap will help you collect the right information that will bring value to your business. Thus, look at the end result you want to achieve; it will help you choose the data to collect.

ERROR #2 – Ignoring the small data

One of the biggest mistakes you can make with Big Data is to stop experimenting. What Big Data does is to tell us about the past (an action or decision made).

So it is a huge error to depend on this as a prediction of the future. Businesses make the mistake of using this information as it is, without experimenting. With the continuous change in consumer preference and market conditions, it is a fatal mistake if you don’t experiment.

The Suggestion…

Keep on experimenting with data collected and watch the market carefully. Consumer preferences change. So what helped you predict a behavior correctly before may not work all the time. A holistic approach works better. This is a combination of both big and small data to get a clearer picture of consumer behavior.

ERROR #3 – Only IT drives Big Data

Most organizations make the mistake of relying on the IT department alone to drive Big Data. But this cannot achieve the goal. Big Data is more of a business decision and practice than an IT drive.

The Suggestion…

To make the most of Big Data in your business, you must involve all departments that need access to data. Departments like finance, marketing or sales need access to data.

ERROR #4 – Depending on the only digital part

Yes, the Big Data technology uses advanced tools to make decisions and to understand the impacts of business efforts. But the entire process is not dependent on the digital. Apart from what happens in the digital space, the analog world is also used to understand the whole process. Both parts are important for successful outcomes.

The Suggestion…

You derive the most interesting data from the physical world. These data can be captured and digitized. You should ensure that intelligence is integrated into the data acquisition process to create a balance.

ERROR R #5 – Slow action on data

To make the most of Big Data, your decision and action must be timely. It is a huge mistake to learn and not act swiftly.

Our Suggestion is…

To maximize Big Data, you must ensure you have a mechanism in place that allows methodic interpretation of data. Additionally, to enjoy a competitive advantage, it is important to ensure that once a decision is made, it is acted on swiftly.


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