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Top 3 Essential Trends in Data Analysis

While the use of connected peripherals is growing within information systems, companies are looking for the way in which they can benefit from the use of data.

While Cloud Computing is now a mature technology and Big Data is on everyone’s lips, analytics specialists have sought to find out what future trends are in this area.

We went through the press and blogs dedicated to the data analysis market and summary a short list of three trends.

Big data and analysis of predictive data

This is the most current trend in data analysis: Big Data. A special feature of Big Data is that it allows capturing interaction data, that is to say it characterizes the interactions between a consumer and a product before, during and after a purchase.

In addition to a better knowledge of the behaviour of current users, the exploitable data and their characterization now make it possible to make further progress in predictions and probabilities. According to a study conducted by Forrester Research in September 2015:

  • 89% of business executives believe that Big Data will revolutionize business operations, and
  • 83% say they have undertaken Big Data projects in order to obtain a competitive advantage.

The combination of Big Data and predictive analytics should enable companies to have new views and data about customers and business processes, add interactions with users and customers, and re-engage the customer with services digital.

Analysis of on-the-fly data flows

Second trend in analytics – analysis of data flows on the fly. While the data comes from multiple sources and terminals , making them increasingly difficult to exploit, and as businesses want to make more and more immediate decisions, data flow processing technologies should concentrate very soon on the possibility of perform real-time event stream processing .

One example is ebay , which has developed its own real-time analysis solution called Pulsar . This solution collects and processes events instantly and with the aim of reacting to the activity of the user in seconds. The ebay teams can thus use this information as part of their advertising, online marketing, invoicing or business activity monitoring strategies. As a result, it is no longer a question of analyzing what has happened in the past, nor of predicting what will happen, but rather of understanding and revealing what is happening now.

To do this, the analysis of data flows is based on three steps: aggregating data in a sliding time window, connecting multiple data streams in motion, checking them over a period of time, continuous data querying.

This technology is particularly useful for risk management, detection and prevention of fraud, anti-money laundering and customer knowledge. The processing of data flows reveals its value when it is integrated into analytical applications. Thanks to the exceptional capabilities of today’s tools, the ideas for operating these real-time data streams are particularly wide.

The exploitation of the data generated by the connected objects

Finally, third and not least, that caused by the advent and generalization of connected objects, capable of producing multitudes of data and metadata. They invade every sector of everyday life, whether it is automotive, energy, home automation or health. The considerable amount of data generated by these connected objects should bring many benefits for companies in terms of customer knowledge, loyalty, knowledge of product usage, or development of new services.

According to a study by Gartner, the market of connected objects will represent by 2020 a turnover of nearly 1,500 billion euros. If questions remain open about the security of the information generated, the impact on consumer privacy or consumer law, it is mainly a revolution in knowledge and automation of marketing.

As an example, Salesforce has developed a new tool for capturing data from these connected objects , such as social flows, application data, Internet data and weather data, in order to obtain a panorama of consumer behaviour and their habits. There is no doubt that companies will find ways to exploit but also monetize this new data.

Thus far, we have just gone through three promising trends in data analysis. Big Data, of course, which can improve the analysis of predictive data, the analysis of data flows on the fly, which allows understanding what happens in real time, or data analysis coming from the connected objects, which has a potential still difficult to imagine as the possibilities are important.

For CIOs, managers need to understand the importance of these new trends, since the control and interpretation of data, the ability to extract information and strategies, are competitive advantages that will enable companies to get their hands on the game at a time when technology is dictating its new rules.

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