As we get ready to bid goodbye to 2015 and gear up to welcome another year, we can’t help but retrospect on how this year turned out to be for the analytical space and what to expect in the future. However, to plan the future it is important to look at the past, and for that matter one needs to compare. Hence, we bring you a mixed palette which makes it interesting to see how different last year analytical trends were from this year as well as what new trends may stem from these.

Analytics India Magazine decided to dig out the best and most popular analytical trends by speaking to those who have experienced the eye of analytics hurricane and continue to win over it diligently. Here’s a glimpse as the data leaders from different companies share the top and emerging trends that rule analytical the industry.

1. Increased use of Digital Marketing and Social Media Analytics

Suhale Kapoor (Executive Vice President and Co-Founder, Absolutdata Research & Analytics Pvt. Ltd), observed a growth in social media analytics and business intelligence through digital marketing. He remarked that digital marketing analytics expenses had increased by 60% in 2015 as branding and advertising businesses boomed.

Likewise, he predicts that social media and online advertising on mobile will continue to grow as integration of offline and online customer experience is on the rise.

“There is a rise in democratizing analytics through cloud and social media”, agreed Sudipta Sen (Regional Director – South East Asia, Vice Chairman and Board Member – SAS Institute (India) Pvt. Ltd.) He added that, cloud helps in making analytics available to more consumers at lower cost. In fact, businesses today derive meaningful insights from social media using the flood of conversations. By turning towards analytics to help them understand customer attitudes and identify trends, they make smarter marketing decisions.

2. Governed data discovery becomes essential

James Richardson (Business Analytics Strategist at Qlik), talks about another emerging trend – Self-service Business Intelligence.

With more data out there, users want to become more self-sufficient in creating their own analyses rather than relying on others, but this means they need to work in a managed data space. Within a framework of governance, users will focus their energy on getting insights from their analyses.

With the ability to combine both internal and external data sources, users now have access to more context around their data, which ultimately leads to more insights and better decisions.

Meanwhile, Lavanya Uppala (Practice Head of Big Data Analytics program at Bosch India), spoke about creating a unified data culture across organizations. Thereby, enabling a variety of analytical applications such as customer experience management, social media monitoring etc.

3. Personalization

Sudipta Sen (Regional Director – South East Asia, Vice Chairman and Board Member – SAS Institute (India) Pvt. Ltd.) identified ‘Personalization’ as an emerging trend. Owing to the advancements in technologies combined with the avalanche of data available today, enterprises across industries are leveraging inexpensive technologies such as Hadoop to analyze huge amounts of customer data, understand patterns and subsequently personalize their offers to their customers. This in turn helps them out-think and out-do the competition.

James Richardson gives us another angle as he believes “More data storytelling equals more engagement”. In fact, when making a proposal to a group, 86 percent almost always or often take time to ‘lay out what has happened previously,’ and 80 percent almost always or often take time to ‘project forward or to predict possible outcomes’.”

He added that storytelling not only personalizes the task at hand, but it can also make it more memorable, impactful, and relevant for those that hear it. In 2016, there will no longer be an excuse to “take that offline.” People will use interactive storytelling to deliver information in a more compelling way that prompts them to take action in the moment, when the insight emerges.

4. Expansion Analytics for Internet of Things (IoT)

This steers us to our next topic – IoT. Now, most of our experts percept that 2015 is witnessing an expansion of the ‘Internet of things’ or the IoT at high rate. Sudipta Sen, said that “More devices than ever before are being connected to the internet today. In fact with over 30 billion devices forecasted to be connected to the internet by 2020, we truly live in an age of Internet of Things (IoT).”

IoT is the concept of everyday objects – from industrial machines to wearable devices, using built-in sensors to gather data and take action on it across a network. To boot, governments and organizations alike are exploring ways to leverage the vast volumes of data generated by these devices and platforms to optimize processes, create differentiated offerings and derive new revenue streams.

Moreover, Rachit Ahuja (Head of Global Marketing, Ma Foi Analytics) contributed by stating that Indian analytics market space now has start-ups providing Internet of Things (IoT), machine learning and NLP based products that can crunch an entire set of big data and use algorithms to come up with accurate and tailored results. He predicts that “this is one of the interesting trends that will catch up in days to come!”

5. Analytics in Education industry: sprouting through MOOCs

Another interesting trend that has been sprouting steadily was spotted by Sray Agarwal (subject matter expert of Business Analytics for TimesPro) and Lavanya Uppala. They agree that universities have started setting up data science and analytics courses as the demand in the industry has increased.

Sray Agarwal remarked that Massive Open Online Courses a.k.a MOOCs are not a new concept for students and professionals. Numerous foreign universities and institutions have launched MOOCs across varied subjects from mathematics to data science. However, in the world of analytics, MOOCs have really changed the way people learn data science. Today, they are not merely recorded videos of professors/trainers talking about data science, but they also uniquely connect with resources such as blogs, groups, discussion boards and forums. They also help hosting meet-ups for the participant for enhanced learning experience.

On the other side, these MOOCs are leveraging the data collected through the participant to improve the content, quality and scope of the delivery. Needless to say, analytics is transforming every business and taking them to greater heights than ever before.

Furthermore, Lavanya explained that even in India, “Many top B-schools and Universities are setting up data science and self-service data discovery courses into their academic curriculum to meet the increasing demands from the industry to produce quality talent pool.”

6. Data Visualization

Moreover, James Richardson remarked that rather than just consuming information, users are now engaging in data prep and profiling. As a result, visualization is now becoming a form of self-expression.

By creating visual apps, users are expressing their views and learning about themselves through being actively engaged with the growing volumes of data. You can see this trend in the rise of the quantified-self movement at an individual level and data-driven journalism in the mass media, altering how people are using public data to understand how society works.

7. Cognitive analytics continuing to drive users

Ms. Lavanya (Practice Head of Big Data Analytics program at Bosch India) pointed out that context-aware cognitive analytics along with its underlying AI and NLP techniques are enhancing the robustness and accuracy to solve complicated business problems without constant human observation.

Therefore, significant developments in cognitive computing can improve the quality of the decisions made for the business users.

Furthermore, Rachit Ahuja contributed to the discussion by claiming that “Consumers will expect their software to anticipate their needs, driving requirements for predictive capabilities in all apps.”

Thus, the goal is to expand the boundaries and our understanding of what it means to assemble and display intelligence ‘in context’. Clients are now looking for embedded predictive analytics with visualization capabilities rather than a separate visualization tool on the backend.

8. Product based analytics

Rachit Ahuja affirms that product based analytics consumption is definitely on the rise. People and departments are increasingly lining up to self-service analytics software — which are easy to use and do not require any technical knowhow.

Conversely, there is a growing shift from project based to outcome based engagement model. Interest in new methodologies, involving semi-structured and unstructured data, e.g. NLP, elastic search and machine learning will see significant rise.

9. Mobility – A screen in the hand is worth two on the desk.

James Richardson, said that Mobility is becoming more important than ever for data users. This means that enabling multi-device lensing of BI and analytics will gain importance. For instance, 85 percent of respondents from the U.S. and 77 percent of respondents from the rest of the world complete their objectives by using multiple devices simultaneously. Having unlimited access to their data can help users ask “why?” any time, and find the answer quickly. BI and visualization solutions that don’t support users moving from device to device, often and at speed, will not deliver the kinds of experience that people want.

10. Predictive analytics in entertainment industry

As we reached the last part of our discussion, Vibha Bhilawadikar (Vice president, Kiesquare) and Sray Agarwal also spoke about predictive analytics in entertainment industry.

Sray Agarwal expressed that previously analytics was utilised only for business purpose and for conventional decision making. However, there has been a paradigm shift in that notion. Based on various attributes that can either be aggregated in-house or through social media, lot of insight on revenue, ratings, audience sizes, movie attendance, number of prints, pre and post release marketing campaigns and even probability of grabbing awards can be revealed using predictive analytics.

However, Vibha Bhilawadikar argued that “while there can be set frameworks with specific protocols, we have to lace all the quantitative analytics with qualitative conversations and pitches to achieve the planned business outcomes.” She strongly believes, from her personal experiences of the same industry, that the business situations that we encounter cannot be negotiated with prescriptive solutioning in its complete totality. So while descriptive analytics is needed for the context of business thinking, predictive analytics is needed for building “what if” scenarios. Therefore, companies have to layer qualitative research in their strategy to accomplish their planned business goals.

Thus, it is interesting to note that Analytics has touched upon all sorts of spheres this year, from education industry to entertainment, it has not restricted to any one sector. We conclude by hoping this compilation would help you reflect on what new trends would stem in 2016 and be better prepared to welcome another new year!