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Home / IT Blogs / The Future of Business Intelligence: 2021 Trends and Predictions
November 12, 2020 - by Synoptek
Every company today relies on data. Given that data can be used to enhance employee satisfaction, improve operations, optimize the supply chain, understand customer behavior, enable predictive maintenance, and more, its importance to the organization’s success is irrefutable. However, given the variety, volume, and velocity of data, the best outcomes from data can only be achieved by embracing Business Intelligence (BI).
Modern BI tools open up a world of opportunities for organizations, empowering them to unearth new insights, efficiencies, and innovations, and become more proactive in carrying out day-to-day business operations. The many capabilities of BI tools are responsible for driving the growth of the BI market, expected to be worth $33.3 billion by 2025. Let’s take a closer look at what the future of business intelligence looks like, and what you can expect out of 2021.
Like every other technology, BI trends are constantly evolving. From early days when BI was confined to spreadsheets bursting with numbers, today, technology allows for insightful visualization and immediate action. Today, BI provides organizations with new and novel ways to improve productivity, increase profits, and understand customers. As technology advances with the blink of the eye, the future of BI looks extremely promising. However, to realize the real value from BI, it is important to be aware of upcoming trends, understand if and how they can be incorporated, and have a roadmap in place to embrace technology across the business.
As regulations across data privacy and security become more stringent, data quality management has become indispensable for business excellence. The coming years will see organizations driving sustained efforts towards classifying data and knowing where it is coming from, who has access to it, how people are using it, and how long they can keep it.
In the realm of BI, data governance will become a top priority for organizations big and small. This will also be driven by the number and complexity of data sources and data types needed to support analytics initiatives that are increasing exponentially. A sound data governance strategy will not only help improve ROI from BI investments; it will also enable a healthy balance between data consistency and transparency – setting the foundation of accurate, ethical, and evidence-based decision-making.
Data governance will enable organizations to clearly understand the information needs of the enterprise, continually improve the quality of data and information while ensuring privacy and confidentiality and preventing unauthorized use. It will allow them to use the right data to guide informed BI decision-making and ultimately improve business outcomes. It will also ensure data is acquired securely from approved sources, processed for the intended purpose, shared with authorized personnel, and discarded as per a pre-defined timeline.
As business users get increasingly tech-savvy, they expect anytime, anywhere access to the data they need to do their jobs well. They want to be able to solve issues on their own – without having to depend on an analytics team. With centralized data from across the organization, users want to use the tool of their choice to drive value.
Although self-service BI is already popular, it will become a global norm in the coming years, enabling users to get the insight they need to tackle challenging business problems in a timely fashion. It will help optimize the decision-making capability across the organizations while powering users with a single version of the truth – in whatever they do.
Since business users know what they want, having a self-service data model will enable them to become self-sufficient. The coming years will witness users make better use of data and pave the way for an organization-wide data culture. Self-service BI will break the dependency on IT/data teams to get access to the right data; users will be able to meet their analytical requests with ease and make critical decisions at a much faster pace.
Although predictive analytics has been an integral aspect of BI that enables organizations to extract information from existing data sets in order to forecast future probabilities, the coming years will witness prescriptive analytics becoming a worldwide feature.
Prescriptive analytics will examine data or content to determine what steps need to be taken to achieve an intended goal. By gauging the impact of future decisions, it will enable organizations to adjust the decisions before they are made – thereby improving decision-making accuracy.
For the next couple of years, organizations will use prescriptive analytics to factor in information about possible situations, available resources, past performance, and so on and get suggestions on the best course of action or strategy. They will understand worst-case scenarios better and make decisions based on highly analyzed facts – rather than jump to conclusions based on instinct.
As the relationship between humans and machines becomes more and more profound, the growth NLP is unprecedented. Although smart voice assistants have long been responding to users through NLP, enterprises will also improve business results to pursue a more significant competitive advantage in the coming years. In a few years, NLP will be used not just in the customer service department, but also in other business areas. For example, NLP will allow not-so-savvy employees to make sense of complicated systems and digital tools. It will also make BI-based data more accessible and enable non-technical users to connect to data – quickly and easily.
Using NLP, businesses will analyze customer sentiments, abstract information from a piece of text, or determine how positive (or negative) social media buzz around them is. The technology will also evolve into AI-powered chatbots, providing quick and accurate answers to users’ BI inquiries.
As the XaaS model permeates into virtually every area of business, the realm of BI and data analytics will be no exception. Companies with humongous amounts of data, but having difficulty accessing the data or driving insights from it, will look out for BI-as-a-Service options. This model will deliver all the benefits of a full-fledged, end-to-end BI solution, but with the ease and simplicity of a cloud deployment.
BI-as-a-Service will enable organizations to get a BI solution up and running in no time while freeing their IT staff from carrying out complex analysis tasks. The model will allow organizations to get ready access to expert BI consultants and data architects who understand data and help manage and govern it to drive better business results – at substantially low costs. Using BI-as-a-Service, organizations can have experts seamlessly extract data from multiple sources, organize and analyze the growing volume of data, and present insights to users using intuitive dashboards and reports. The end-to-end service will not only enable them to overcome bottlenecks around their small number of data scientists; it will also allow everyday users to create reports and dashboards on their own.
The coming years will witness collaborative and integrative BI become increasingly mainstream. Unlike today when stand-alone BI tools must be purchased and implemented separately, most enterprise systems will have built-in BI capabilities, so users can unearth insights and make decisions – without ever leaving the platform.
The next-generation BI systems will be geared toward larger sets of users and more connected to bigger enterprise systems. They will continuously pull data from the required sources, consolidate, and analyze it and present users with the required insights – in real-time. These systems will also be capable of sending alerts to users, updating them with changes to the data at hand.
By becoming increasingly embedded in existing (and upcoming) workflows, these systems will allow teams of employees to carry out their day-to-day operations and make decisions through the exploration of data in real-time. In addition to allowing for data analysis within existing systems, they will also integrate seamlessly with third-party systems – therefore, paving the way for an enterprise-wide, data-driven culture.
Companies who want to stay on the right side of the digital disruption must move fast and get serious about their data and analytics efforts. While much of the data analysis going on today is based on historical data, the focus is rapidly shifting towards a more forward-looking (and even automated) data-driven decision-making. As the BI landscape is soon going to be defined by trends around data governance, self-service BI, prescriptive analytics, NLP, BI-as-a-Service, and collaborative and integrative BI, organizations must embrace these trends and strengthen their foothold in today’s competitive and dynamic business environment.
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