What makes data analytics so hard today is the amount of data you get from different sources and trying to figure out what is important for your business, and discard the rest.

A wide range of software, technologies, and strategies are available to address these issues of big data, unstructured data, and they are rapidly evolving. In order to maximize your investment in data analytics, you need to be aware of the trends to choose the right ones for you.

Here are the seven top analytics trends of 2018.

1. BOTs invade the enterprise. Organizations will focus on adoption of tools that will usher the next wave of enterprise automation. Efficiency based tools and robotic process automation (RPA) will eliminate tedious and effort intensive tasks while Artificial Intelligence and machine learning techniques will take over the complex, cognitive intensive tasks.

2. Conversational interfaces will lead to wide spread adoption of analytics. Having a natural conversation and getting answers to not only weather & traffic updates, but also financial operational metrics, can transform both businesses and the consumer space. 25% of enterprises will supplement point-and-click analytics with conversational interfaces. Querying data using natural language and delivering resulting visualizations in real time will become standard feature of analytical applications.

3. Insights as a service. Analytics will increasingly get deployed with a variety of services available for every task in the analytics pipeline through libraries on the cloud or APIs. The focus will shift to looping together these services across tools, to deliver insights in a lightweight model. This will signal a shift away from expensive monolithic tools or custom development.
The insights as a service market will double as insight subscriptions gain traction. Forrester research predicts that up to 80% of firms will rely on insights service providers for some portion of their insights capabilities in 2018.

4. AI will erase boundaries between structured and unstructured data based insights. The number of enterprises with more than 100 terabytes of unstructured data has doubled since 2016. However, as older generation text analytics platforms are so complex, only 32% of the companies have successfully analyzed text data, and even fewer are analyzing other unstructured sources. This is about to change as deep learning has made analyzing this type of data more accurate and scalable.
20% of enterprises will deploy AI to make decisions and provide real-time instructions. AI will suggest what to offer customers, recommend terms to give suppliers, and instruct employees on what to say and do in real time.

5. Contextual insights will be delivered in real time. Using machine learning algorithms business users will take advantage of contextual insight delivered by their applications at the most advantageous moment with relevant context. Customer churn analysis, workforce planning, sales compensation, and supply chain logistics are just a few examples that will benefit from timely insights delivered to users in context within their application workflow.

6. Deep dive for better understanding. Machine learning and neural network algorithms are the basic concepts driving data analytics today. A standard neural network has a few layers, a deep neural network goes down the hidden layers as far as it can go.

It may alternate up to 20 layers of nonlinear and linear processing units, recognizing more patterns and connections as it goes. It takes more time to learn the framework to collect and analyze the data, but you have much more robust predictions.

7. Behavioral Analytics. It’s about analyzing consumer behavior that help enterprises to detect what their customers want and how they might react in future. Analyzing the interactions and dynamics between processes, machines and equipment, even macroeconomic trends, yields new concepts of operational risks and opportunities. Matching customers with analysis from “digital twins” provides further insights into patterns, which in turn provide organizations with an opportunity to enhance customer experience.