Big, bigger, biggest: Top big data trends for 2017

We hear a lot about big data and its influence on IT, enterprises, and various businesses. In fact, it is currently one of the most talked-about subjects in technology. With the advent of big data, the world is witnessing a major shakeup in the processing and analysis of data.

The term “big data” is meant to describe very large volumes of both structured and unstructured data that can be analyzed to discover patterns and trends, especially in how humans act and interact. These datasets are extremely complex and are typically so large that traditional data-processing programs that businesses relied on for years are incapable of handling them. The concept started gaining popularity and momentum back in the early 2000s, and since then it has been shaping businesses on a day-to-day basis. Big data now plays a vital role in analyzing huge volumes of data and aids in helping organizations make better decisions and more strategic moves.

In 2016, we witnessed some major strides and exciting changes in big data and analytics. Considering the pace at which big data has been evolving in recent years, we can expect more advancements and innovations in various fields of the IT industry. Here are some of the top big data trends to watch out for in 2017:

Better and stronger data security

Ever since we started depending on digital technology in almost all our daily tasks, cyberattacks have also grown in number and are now much more common and rampant. Attackers now are not just concerned about the global financial institutions but have started targeting the personal data of businesses and ordinary individuals for ransom. But as cyberattacks increase, big-data analytics is being mobilized to prevent the attacks and find the hackers.

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Big data can not only classify and categorize cyberattacks quickly but can also help business analysts visualize these cyberattacks before they happen. This visualization can be done by considering the complexity and attack patterns from various sources. Following these patterns, we can predict similar cyberattacks in the near future, thus taking steps to safeguard systems and privacy.

In the case of enterprise-level large data warehouses and repositories, ramping up security and also tightening access permissions can be achieved using big data. Big data analytics also ensures that every user has just the right and required data access privileges. Considering previous cyberattacks, it is likely that from now on, both private and government organizations of all shapes and sizes will address these security issues. And with big data offering a flexible analysis of these threats with the filtering, classification, and analysis of data, it is going to be one of the better available options for companies to opt for.

Growth of analytics

With big data gaining momentum in various fields, 2016 witnessed the rise of faster, more precise, and more advanced data analytics in fields such as IT, finance, health, and more. Currently, almost all IT firms and businesses have started using data analytics to fetch the right metrics for the betterment of the business. Analytics also provides immediate actionable data without having to wait for the cumbersome and time-consuming batch analytic reports.

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Building on the gains we’ve made, analytics is an ever-evolving field and will get even more powerful. Although we currently have efficient tools and reliable data warehouses, the complexity of data analysis hasn’t been reduced. With the amount of data increasing rapidly, the algorithms and methodologies to analyze this data also need to increase, and as analytics has an important role in business, we can definitely expect more analytical innovations in 2017 and beyond. Here are a few of them:

Faster, more secure financial transactions

Big data has already started paving the way for innovation in various fields, especially banking and financials. With advanced big data analytics, the banking sector has evolved tremendously over the recent years in terms of their operations and service deliveries.

Big data analytics makes it easy and convenient for banks to keep track of the transactional records and also enables them to keep proper purchase tracking. With the increasing number of transactions performed on various forms of banking, we sometimes tend to face a lag in the payment processing system or a delay in operations. And, of course, there is the ever-present threat of fraudulent activities in banking, especially on online platforms. Most banks have already started to address these issues with the help of cloud and big data analytics. The cloud paired with big data provides a huge opportunity for the evolution of banking sector.

Thanks to the advancing big data analytics, we are seeing a significant development in the financial industry especially in online banking, stock purchases, credit/debit card payments, and more.

Big data can not only address most of the common issues but can also provide numerous other advantages to both banks and customers. Here are some of them:

  • Fraud detection and prevention can be made easy.
  • Faster and more efficient operational efficiencies.
  • Easy customer segmentation.
  • Risk management.
  • Easy integration of data and security.

Artificial intelligence

Artificial intelligence is now one of the mainstreams of the IT industry. From toy makers to automobile manufacturers, companies have already started using AI to improve their products.

The future of AI depends largely on big data analytics. Machine learning is a key to achieving milestones in AI, and data analytics serves as a vital source in achieving this. With increasing data transfer speeds, security, data indexing, multiplatform integrations, and data sharing, artificial intelligence is getting faster, more secure, and more accurate than ever.

Many companies have already started using artificial intelligence to create their own “avatars,” serving as digital assistants to interact with users. This will not only save human efforts, but is aimed at providing unbiased, reliable, and accurate assistance. This can be achieved by analyzing large data patterns and feeding these tracked patterns into the systems. Apart from this, there are various other applications and advantages of integrating big data with artificial intelligence. Some of them are error reductions, wider data exploration, applications in digital applications and medical applications, and, most important of all, this will also automate most of our day-to-day activities.

Internet of Things

Internet of Things is already well on its way to revolutionizing the world. Be it your personal virtual assistants, remote-controlled home appliances, drones, or automobiles, all the IoT-based devices will get even smarter this year.

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With more and more devices being added to the IoT’s menu every year, massive chunks of data are hitting datacenters of IoT-based companies. These datacenters must be able to handle the enormous amounts of heterogeneous data coming from various sources. As a solution to this, big data provides a flexible, sophisticated, and scalable architecture to handle and manage the valuable IoT data. With big data and IoT together in action, we can expect to witness a better and more consolidated IT market with a scope for process improvisations. We can expect organizations to focus on big data for the aggregation and handling of IoT data.

And there’s much more to come

Apart from all these trends, big data will also aid us in making better business decisions. Many of the IT pioneers have already analyzed the advantages and benefits of implementing big data in their businesses and organizations. Now everyone among us needs to understand the importance of big data and its role in tackling the future analytic endeavors. This year, we will see big data extend its functionality into several new fields and companies.

As an IT pro, get ready. If your company isn’t already harnessing big data to solve problems and find solutions, it probably will very soon.

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