Last year I predicted increased adoption of big data analytics in the cloud, along with continued investment and effort by cloud vendors to offer new solutions, especially with the graph data market growing hot. Indeed 2018 was a major year for big data analytics and the graph database market, as we saw new releases, as well as continued adoption and breakthrough use cases of graph analytics by organizations across the world.
So what’s in store for 2019? Here are my top three predictions below. Once again, graph analytics will have a key part in shaping what’s to come.
Big Data and Analytics: A New Shift
The year ahead will see a new focus in big data and analytics, marked by a shift away from building massive data lakes to extracting as much value possible from them. Enterprises and governments alike will closely consider how to best leverage their multi-million dollar investments in Hadoop data lakes to maximize true value.
By tapping into connections within the data, such as relationships between customers, suppliers, products and locations, these organizations can derive new insights using technology like graph analytics to promote better business outcomes. We’ll see more organizations derive value from their data to increase revenue, improve risks and operational efficiency, and to inform areas such as marketing and upsell opportunities.
Real-Time Analytics: Making the Cloud Stickier
The cloud market share grab will continue among top players (AWS, Microsoft Azure, Google Cloud, Alibaba Cloud, etc.) with those providing the most compelling business and IT applications also increasing their market share. This is where complex real-time analytics solutions, such as graph analytics, will take the wheel in driving stickiness for the cloud platform. Expect actionable insights from data in the cloud to propel more concrete business outcomes. In 2019, we will finally see this as a focus among CIOs and CFOs as they make their cloud platform decisions.
Explainable AI’s Role in Revealing Bias
Explainable AI – AI whose actions can be easily understood by humans – will come into its own next year. More and more enterprise and government organizations will demand visibility into how AI applications arrive at their answers.
As biases – both known and unknown – that are introduced by data or algorithms must be revealed, explainable AI provides the logical answer. Explainable AI requires features with well-defined business logic that influence the outcomes – this is where graph-based analytics will become a first class citizen of the AI and analytics mashup in 2019.
The ability to understand hubs of influence – whether it’s from customers, professionals, bloggers and more – and the community around those hubs is becoming a key differentiator and driver for most businesses. The ‘Googlization’ of enterprises and government organizations starts in earnest, with both the private and public sector looking at data science as their competitive differentiator.
