Changes in the digital world and development of new technologies directly have an impact on the digital analytics space. Businesses are perpetually questioning all the decisions they make. They want to optimize each process, reduce the time taken for every activity, generate the maximum returns from their investments; and analytics is the key that can unlock all these benefits. But to deal with the data deluge, organizations are shunning the traditional ways and increasingly opting for actionable and quick analytics at every step of their digital journey.
Here are the top 10 trends that we saw in 2015 and we are sure that these trends will have a big impact on how the coming year turns out to be.
Big data has finally arrived2015 was undoubtedly the year of big data analytics and many of the trends listed below are somehow connected to it. As companies started realizing the potential that big data holds, they began investing heavily in big data analytics. Big data is extremely complex, massive and diverse, but it enables organizations to recognize new insights and innovation opportunities that were never thought of with the traditional data. According to IDC, Big Data Analytics services market is growing six times faster than the entire IT sector and the cloud-based big data analytics is growing three times faster than the on-premise solutions. So, the reign of big data 2.0 is upon us and the coming year will see a further rise in its adoption.
The Internet of Things (IoT) is generating a massive amount of data that needs to be analyzed effectively for further product innovation. According to Gartner, the number of connected devices to the internet would be more than 25 billion by 2020. Currently, descriptive nature of analytics prevails in this domain where information about each individual device performance can be obtained, but the future is about analyzing the functioning of these devices when working along with other compatible devices. So, the next step is connected analytics of the connected devices. Analytics of things can help in identifying deviations and trends, predictive asset maintenance, optimization, prescription, and much more.
The picture is quite clear, 61% merchants are not able to get information fast enough to react to what’s happening in the market. With the rise and rise of data and big data, the most important requirement is to shrink the window of time-to-insight. With better data governance, automation of various parts of the analytics engine, and advancement in big data analytics technologies real-time insights are now a convenient possibility. Businesses have realized that just pooling raw data in the data lakes makes it extremely difficult to utilize. However, with pre-processing, denormalization, and enrichment of data before putting it into the data lakes makes it easier to retrieve, thereby enabling real-time analytics.
Multi-channel retail is the biggest development that happened in the past two years. Customers move through a greater number of touch-points in their path-to-purchase and leave behind a trail of information that can provide endless insights and opportunities for optimization. “Datafication” is the new buzzword in the industry which means that organizations today are pooling vast and varied sources of data into centralized locations and quantifying it for better analytics. Datafication is taking multi-channel analytics to a new level. It helps businesses to prioritize channels and identify the role every path plays in each conversion.
Data presented in beautiful diagrams and charts with color-coded fields is the preference of today’s entrepreneurs. In fact, the human brain is wired to understand visual data better than the numerical one; no wonder infographics have seen a large-scale approval across the digital world. It’s much easier to perceive trends/patterns and drill-down with various fields and parameters through data visualization technologies. In 2015, smart data visualizations achieved a new high, thanks to a great variety of tools available in the market (like Tableau and Qlikview).
Social media is changing every day. According to a recent study, the social media analytics market will reach $2.73 Billion in 2019, at a CAGR of 34.5%. Twitter and Facebook have become old news with next generation social media applications like WhatsApp, SnapChat, Pinterest, and Tinder. The entire social media is quickly shifting to mobile and this shift will impact how analytics is conducted. However, the good news is that social media offers the best measurement techniques and analytical capabilities than any other medium. The big need is to effectively connect social media analytics with all the other sources of data to get a coherent picture. Businesses also need a deep-dive analysis of social data to support affinity-based targeting.
2015 saw some of the biggest hacks and breaches that had a widespread impact globally. Organizations have become extremely anxious when it comes to the security of their data and 2016 will see even more investments in this arena. Although 87% of IT decision-makers feel that they are confident about their organization’s perimeter security, but the reality is that only 8% of the data is protected by encryption. Analytics tools and analytics service providers would need to tighten their reins and ensure harder data security best practices to ensure the safety of customer data.
According to Pew Research Center Smartphone mobile data traffic is growing at a compounded annual growth rate of 119%. And as per a Gartner report, in 2015 mobile app development projects outnumbered native PC app development projects by a ratio of 4:1. Further, mobile usage is growing by 76% year on year. All this is leading to an exponential growth in the amount of mobile data generation. This mandates the need of developing deep expertise in mobile web analytics and mobile app analytics.
Although in early stages currently, cognitive analytics would be the most important domain in the next few years. Machine-to-machine learning and big data are creating opportunities for automated decision making. Complex event processing (CEP) and automated workflows are supporting these technologies. These include machine learning, natural language processing, and an advanced analytics infrastructure. Although, the stage where the machine takes the decision is quite far off, cognitive analytics will definitely enable humans to take better and faster decisions in the coming year.
2015 saw a rise in practical usage of predictive analytics, but a new kid is already on the block. Currently, the penetration of prescriptive analytics is only 1-5% according to Gartner, but the future is very bright as prescriptive analytics is a step ahead and recommends the best option out of the various action choices available based on analytics. The penetration of predictive analytics is 15-25% and is growing. Both predictive and prescriptive analytics are going to be strong in the coming year.
The year 2016 would be big for all domains of analytics. According to the A.T. Kearney 2015 Leadership Excellence in Analytic Practices, “Companies will need 33 percent more talent in analytics over the next five years, across all industries. There are already 10% unfilled analytics related positions and this talent scarcity will grow even larger as organizations embrace analytics and get ready for better data governance.