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Big Data: present and future challenges 

Image of big data code

Big Data: present and future challenges 

In our first blog “Big Data “Basic guide to understand it” we highlight the main contributions to companies, related to increased productivity and decision making. We also talked about successful cases of renowned companies that have interpreted Big Data as a tool to increase their competitiveness. And not only as an instrument to collect information

This time, we will go beyond the concept in general and we will take a look at the current situation. We will talk about Big Data strategies that are key to turn a company into a profitable business and about how to face the challenges Big Data represents in the future.

Today, experts such as Nick Heudecker, Research Director at Gartner, affirm that, although investment in this technology has increased, its growth rate has been slowing down. This is because organizations still see Big Data as a stand-alone effort, rather than as a fusion of technologies and data management best practices capable of supporting multiple analytics use cases. 

Many companies have stalled in the pilot phase, and this may be related to a lack of prioritization of investment against other IT initiatives, which in turn, is related to the lack of return on investment. But one thing is what companies consider not so positive factors and another is the reality. The lack of leadership and encouragement of participation in data-related issues is a reality in companies nowadays. Something essential to make right strategic decisions.

What is the reality?

Gartner defines Big Data as a large volume, velocity or variety of information that demands cost-effective and innovative ways of managing information to make forward-looking decisions based on the present. Please, pay attention to the word “management”. 

In few words, it means that data is just an input. It is true that any organization can access millions of information, from different sources, but it is a worthless resource unless they know how to discover valuable information that drives the fulfillment of the objective. So it is important to know how to manage that information to uncover the golden nugget, and this is where stands out the epicenter of the challenge of taking on Big Data as a business strategy.  

Companies must understand that successful decisions today are predictive, not reactive. Big Data requires an agile approach to information governance. The key is not about collecting, the key is data management. Understanding the concept as a package, as a set of tools that, together with techniques and talent, will lead to a positive evolution. 

Companies must understand that the industry is changing rapidly and the only way to establish a competitive advantage with Big Data is adapt it to the speed of its evolution and execution, as planned. In other words, they must focus their efforts on the three characteristics that are the main challenge, better known as the 3V’s of Big Data: volume, variety, and velocity, without losing focus on management. 

Big data blog

Volume: of course related to quantity. Everything that is constantly collected, regardless of its quality. Organizations generate internal data but also external data coming from different origins or sources such as social networks, interaction with customers, business negotiations or users’ interaction, for example an Ecommerce. The challenge is to have the capacity and knowledge to manage these high volumes of data. 

Variety: Inputs are not homogeneous. Not all data can be processed in a single way. It must have a defined structure and a clear organization, otherwise the visualization of the information is compromised. The challenge is to have enough clarity to process data of multiple forms, types and sources, having a clear objective. 

Velocity: is the agility with which organizations create, access, store and process data. This is essential for them to make the right decisions based on the information gathered. There are occasions when speed is key, for example in the detection of a cyber-attack. The challenge is to work in real time and to have an agile data analysis capacity. 

Since more organizations are adopting Big Data, it is said that a fourth “V” has been born, although it has been a topic of discussion by engineers and developers because it is more aligned with the characterization of data and not with the processing, but in our opinion, it is the one that should be considered the most important: veracity. 

Veracity: Is the data reliable and suitable for your organization’s purpose? Without a reliable source, bad decisions could be made. Falling into the error of interpreting incorrect data could unleash a disaster. The challenge is to intelligently manage the analysis of the high volume of data in order to obtain accurate and useful information. 

It is worth to highlight that many people talk about other additional V’s such as: volatility, value, viability and visualization. Some refer to the 3Vs, others to the 5Vs, and even to the 6Vs. The truth is that each company must classify their importance according to its strategy, purpose and objectives. It is acceptable that not all organizations choose the same methodology. 

The most important question to ask yourself is: How truthful is my data? How much can I trust it? Is there certainty about the collection of relevant data? Identifying the true value of Big Data is not just about analyzing data. It must be a whole process of adaptation and discovery that, of course, presents additional challenges that vary depending on the industry your business is in, which means a completely different approach to deal with problems.

What challenges does Big Data represent for industries?


Although it is true that it promises a great future, it is also true that those who take the initiative to assume it, are facing significant challenges, especially large industries that produce large amounts of information. We are talking about growth at a rate of 40 to 60% per year and according to Gartner, 90% of the world’s data has been created in the last three years. 

Industries such as financial services, retail, healthcare, telecommunications, manufacturing, oil and gas, have been capitalizing Big Data to deliver business scalability and improve the customer experience, but on this opportunity we will highlight the challenges it represents.

Bog Data blog

For example, forward-thinking banks and financial services companies are capitalizing on macro data and have turned it into a competitive advantage. Big Data helps them identify fraud patterns, control money laundering, and comply with financial laws and regulations that require very detailed reporting. Their big challenge is the speed of data management to create advanced risk models without negatively affecting other projects. 

With Big Data, retail companies have been able to project demand forecasts, predict product rotation and even optimize stores for a better customer experience. With an additional advantage, they have been able to identify the reality about customer profitability, leveraging the data for margin and profit analysis. Their big challenge is how to create sophisticated models that examine past customer behavior and predict future actions. 

In the telecommunications industry, Big Data has played a key role as an opportunity for expansion and growth. It helps to plan investments in infrastructure and restructure services to obtain greater customer satisfaction and retain their loyalty, reducing the risk of service dropout to significant levels. The big challenge is how to create display segments according to customer behavior to predict rotation. 

Big Data blog

Big Data is projected as a new driver of the global economy

According to the Data Age 2025 study by analyst firm IDC, by 2025 the generation of information will reach 163 zettabytes, mostly produced by the IoT. An impressive amount, considering that 1 zettabyte is equivalent to one billion gigabytes. The estimation is based on the interaction of people with devices. It is expected that, by that year, an average person will interact with a connected device every 18 seconds, which translates to approximately 4,800 times per day. 

In this context, with the projected statistics, Big Data is positioned as the best solution to help organizations to extract data from different sources, make them meaningful, take advantage and use it to identify new opportunities, of course, as long as organizations know how to manage this avalanche of data we are going through and that, it seems, will continue at a high level.

It is true that Big Data promises great benefits, but it is also true that today it represents major challenges for many industries. Organizations continue struggling to keep up with the pace of their data growth and to find ways to store it efficiently. Managing massive volumes of data is not an easy job, unquestionably it will remain very challenging, but it must be mastered to deliver the expected results. 

To conclude, if organizations apply Big Data management properly, valuing the efforts made in resources, investment and time invested, the results in terms of monetizing information will be as expected, or better, it will exceed your expectations.

At Interfaz we offer Big Data analysis and provide modern solutions for handling large amounts of structured and unstructured data on a large scale. How about working together? Get to know us here.

Resource: Gartner | Oracle | IBM