Business Intelligence and Analytics technologies have continuously evolved because undoubtedly, a business of any size understands the importance of not only availability of data, but how to use the data intelligently for gaining a competitive edge. The ability to efficiently and effectively use enterprise data is often what differentiates an enterprise from its competitors. It benefits businesses in aligning growth strategies, streamline operations, get insights into customer behavior and essentially everything that helps in an enterprises’ digital transformation initiatives. For this reason, it is important for enterprises to keep abreast of trends and innovations in the BI and Analytics technologies and utilize it for their benefit. Some of the key recent trends that have influenced business’ data strategy are illustrated here.
1. Artificial Intelligence (AI) In the Strategic Technology Trends Report for 2017, Gartner has ranked AI at the top of the table. With the availability of mainstream machine learning and AI technology, it is no longer for use only by large, complex scientific applications or high-end gaming. With the ability to learn and adapt automatically, AI provides a strong differentiator to conventional reporting technology. In addition to uses of AI for virtual assistance to dynamically report and adjust marketing campaigns based on real-time responses from customers. The ability to utilize unstructured data and generate relevant insights provide great advantages and opportunities to enterprises.
2. Predictive and Pervasive Analytics It is the process of extracting organizational data, study customer behavior in the past and predict the potential outcomes. As the businesses are always on the lookout for things that will happen in future and the ways to handle the upcoming challenges, predictive analytics has become a boon for them. Pervasive analytics uses the ubiquitously available business analytics and enables business decision-makers to come up with strategies for better customer experience, operational efficiency, and high growth. The use of predictive and pervasive analytics is across industries and segments. It can be used for customer retention, behavior-based advertising, insurance buying decisions, fraud detection in financial applications etc.
3. Cloud Analytics Cloud analytics is not very new to the technology world. However, with more and more BI analytics companies moving with the cloud, it will surely be a key trend in the upcoming years. There has been a decline in the number of companies opting for in-premise analytics software. Instead, enterprises are comfortable in renting cloud base SaaS applications to meet their analytics needs. Cloud analytics not only reduces the total cost, but also offers robust data foundation, reliable insights, improves collaboration, easy to use and fast adoption, scalability, and elasticity.
4. Visual Data Analytics The amount of data generated every day sometimes seems impenetrable even by the data scientists. Analysts are using various data visualization tools like Tableau, Qlikview to gain insight into data relationships and have a better interpretation of analytical results. Visual data discovery is the process of finding inherent patterns between the data item. It is a very effective way of improving the ability to grasp information hiding in the data. Use of visualization tools further helps to create meaningful dashboards and illustrate data stories. It helps businesses to manipulate data directly, identify the trend faster, visualize the relationship between different operation activities, and foster a new way to share the story through the data.
5. Embedded Business Analytics There are numerous analytics tools available in the market, each offering its own advantages and catering to specific domain or segment. Embedded business analytics focuses on the integration of one tool with another or the integration of a BI tool into a mainstream application to overcome the mutual shortcomings in solving a problem. Embedded BI enables the business analysts to build interactive dashboards and innovative real-time analytics solutions. It essentially focuses and helps on Self Service BI allowing end users to easily leverage the power of BI Tools. At a superior level, embedded BI can be part of workflow automation, such that critical actions are triggered automatically on the basis of a framework developed by the end users or decision makers.