Information Activism Will Rise In 2017: Qlik
While the year 2016 was a breakthrough year for Data analytics , the innovations in the space will continue to transform the way businesses harness the insights into information to improve business efficiency in 2017. According to the Markets And Markets report, the big data market is expected to grow from USD 28.65 Billion in 2016 to USD 66.79 Billion by 2021, at a CAGR of 18.45 percent.
While companies will continue to adopt data analytics in a big way, they will move towards a model where businesses have combination of different sets of data. Since, there is ample availability of BI tools, information activism will be on the rise in 2017. More importantly, organizations’ focus will shift from “advanced analytics” to “advancing analytics.” in 2017.
Qlik, the business intelligence & visualization software has listed out top Analytics predictions for 2017.
# Combinations of data: With more fragmentation of data and most of it created externally in the cloud, there will be a cost impact to hoarding data without a clear purpose. That means companies will move towards a model where businesses have to quickly combine their big data with small data so they can gain insights and context to get value from it as quickly as possible. Combining data will also shine a light on false information more easily, improving data accuracy as well as understanding.
# Hybrid thinking – In 2017, hybrid cloud and multi-platform will emerge as the primary model for data analytics. Because of where data is generated, ease of getting started, and its ability to scale, we are now seeing an accelerated move to cloud. But one cloud is not enough, because the data and workloads won’t be in one platform. In addition, data gravity also means that on premise has long staying power. Hybrid and multi-environment will emerge as the dominant model, meaning workloads and publishing will happen across cloud and on-premise.
# Self-service for all – Freemium is the new normal, so 2017 will be the year users have easier access to their analytics. More and more data visualization tools are available at low cost, or even for free, so some form of analytics will become accessible across the workforce. With more people beginning their analytics journey, data literacy rates will naturally increase — more people will know what they are looking at and what it means for their organization. That means information activism will rise too.
# Scale-up – Much a result of its own success, user-driven data discovery from two years ago has become today’s enterprise-wide BI. In 2017, this will evolve to replace archaic reporting-first platforms. As modern BI becomes the new reference architecture, it will open more self-service data analysis to more people. It also puts different requirements on the back end for scale, performance, governance, and security.
# Advancing analytics – In 2017, the focus will shift from “advanced analytics” to “advancing analytics.” Advanced analytics is critical, but the creation of the models, as well as the governance and curation of them, is dependent on highly-skilled experts. However, many more should be able to benefit from those models once they are created, meaning that they can be brought into self-service tools. In addition, analytics can be advanced by increased intelligence being embedded into software, removing complexity and chaperoning insights. But the analytical journey shouldn’t be a black box or too prescriptive. There is a lot of hype around “artificial intelligence,” but it will often serve best as an augmentation rather than replacement of human analysis because it’s equally important to keep asking the right questions as it is to provide the answers.
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