Understand Big Data And Its New Challenges

Understand Big Data And Its New Challenges

There is a lot of talk about the importance of big data in business and it is not new that it can help companies achieve promising results.

However, as much as the term is being widely propagated, its concept still raises many doubts.

In this post, we call on the team of experts here at Indicium to answer the main questions on the following subject.

So, read on to understand all about it.

What is big data?

Big data is much more than a technology.

It is datasets (datasets, in English) generated in large volume, variety, and velocity, which can not be stored, processed, or resolved by traditional databases and software, such as Excel.

Furthermore, it is a concept that encompasses the ability to collect, analyze and understand data generated on a daily basis. In other words, it only becomes a resource for those who know how to manage it efficiently, so that it is possible to carry out assertive analyzes and get answers in real-time.

The 5 Vs of Big Data

Not every dataset is big data.

There are three fundamental characteristics for understanding, known as the 3Vs of big data. They are volume, variety, speed.

Let’s explain better!

Big data is characterized by a large amount of data, which can range from terabytes to zettabytes. In addition, it includes a huge variety of data in different formats (structured, hybrid, semi-structured, etc.), which can be processed at high speed.

But not only that. Recently, two more Vs have been added to the big data literature: veracity and value.

The truth is an essential element in all big data processes and can be considered the most important V, since without it is not possible to achieve expected business results. It concerns the reliability of the information retained in the data.

If you base your analysis on outdated or erroneous information, your company’s decision-making will never be assertive. So, to exploit its true advantages, you need to ensure that this data is trustworthy.

Finally, it needs to bring value to the business. And, for that, it is necessary to follow a series of complex analytical processes, until transforming the data into relevant information.

It is not enough to have data, they have to serve a business purpose, such as discovering and predicting market opportunities, creating new products, etc.

How did big data come about?

Long before big data, data management has always been an important aspect of the business world. Companies already had consolidated processes to deal with them, even without the new technologies.

However, processing and storage costs were absurdly high. As a result, many organizations could not efficiently collect, store and analyze data.

In the early 2000s, there was an exponential growth in data generation and, as a result, the real importance of exploring the information contained in these large datasets was realized.

This need has fostered the emergence of technologies that have made storage and data management more cheap, affordable, and scalable.

From then on, big data gained more prominence in the market. And since then, new technologies such as machine learning (ML), the internet of things (IoT), and artificial intelligence (AI) have expanded their possibilities even further.

Does your business need big data?

To answer this, you need to understand the characteristics of the data stored in your business.

  • What are the volume, variety, and speed of your data?
  • Is there truth in them?
  • Do they deliver value to your company?

There is no single answer to these questions.

But one thing is certain: for a company to take advantage of big data, its database must be classified as such. That is, it needs to contemplate the 5Vs.

Therefore, if your company already has a significant amount of data, the great benefit of bigdata is the value it generates:

transforming thousands of pieces of information into powerful business insights.

For example, a consistent big data strategy can help your organization:

  • reduce operating costs.
  • increase your performance.
  • open up new business opportunities.

What if your company does not have these characteristics?

Have you ever heard about small data?

In a big data world, little is said about it, but it is also a dataset. However, it can fit inside an oven, a medicine bag, or a Facebook photo album.

It is any small data set used for decision making, which can be compiled into a simple system such as an Excel spreadsheet.

We can extract information from small data just as we do from big data. The processes used may vary, but the end is the same: to gain insights from the data.

Therefore, small information, when collected and analyzed correctly, can also achieve great business results.

The true potential of big data

Today, companies store, manage and analyze your big data so efficiently and with reduced costs and can innovate and explore new ways to capture and analyze the steady growth of the dataset (which tends to accelerate more and more).

The business intelligence and value of this come precisely from the possibilities it delivers when combined with data analytics. This allows:

  • understand and predict customer behavior.
  • reduce costs.
  • process optimizations and decision making.
  • improve business performance.
  • detect fraud.

Also, with the radical cheapening of data storage, it became possible to store virtually any and all data generated by organizations. You no longer have to worry about having to invest a considerable portion of your budget in data collection tools and processes.

The new challenges of big data

Despite all these promises, data also brings challenges.

How to organize, process, and understand this extraordinary volume of data generated today?

After all, the true value of big data only comes with the implementation of a consistent process of collecting, processing, and querying the company’s data. And this is only possible through the best practices of processes and technology.

Also read: Why Can They Block A Bank Card And How To Solve The Problem?


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