No one doubts the value of data and data analytics for companies, however, its use still has a lot of room for improvement. Emerging trends, such as artificial intelligence or machine learning, are beginning to be considered as a key to help obtain greater value from them. And it seems that 2021 is going to be a year of inflexion in this regard. It is time that we evaluate AI Strategy and plan that will help businesses to automate processes, create new products, or improve existing products.
At Information Builders we have compiled these five key trends around data and analytics that can help us take our business to the next level:
– Data and analytics, the powerful duet: We still tend to handle data and data analytics separately, but to achieve success in analytics you need a solid data management. Both lines are necessary for success, and companies must develop cohesive strategies so that, together, they help them obtain more refined and interesting results for the business. From the point of view of the solution provider, we will see how support for a complete approach to data will continue to improve. Companies demand the ability to manage data intuitively, and this will lead to a convergence of data and analytical strategies.
We still tend to handle data and data analytics separately, but to achieve successful analytics we need a solid data management
– The next generation of embedded analytics takes the customer experience to a new level: Embedded analytics is becoming the norm for all users of the organization to have access to operational information. According to the Dresner Advisory market study, Embedded Business Intelligence Market Study, more than 90% of respondents think that embedded analytics is important for their analytics environment. For its part, Ventana Research estimates that by 2021, more than half of the analytics developments will be carried out using embedded analytics. We will see how the next generation of applications will already have built-in analytics since its inception, thus offering quantitative value and therefore allowing customers to have greater visibility and better user experience.
– Smart ecosystems redefine the data strategy: Big data, IoT, and the rest of diverse data sources are leading to more complex data ecosystems. And they are not the only ones, with the growth of smart cities, autonomous vehicles, sensor data for supply chain management, chatbots, etc., we will begin to see a growing number of autonomous ecosystems. The integration of these different types of data, together with greater digitization and automation will change the way we interact with technology. In sectors such as manufacturing, supply chain or healthcare, applications are more obvious, since data collection is already analytically based. But little by little the interactive and intuitive technologies that we use in our personal lives will also begin to converge more widely in companies,
– Artificial intelligence will be helped by human intelligence: There is a certain fear in society that AI and robots take over our jobs and change the way we work and interact with technology. There is some truth to it. There will be changes and the level of automation within society will grow, probably certain sectors and jobs will be replaced. But at the same time, although computers will learn on their own thanks to artificial intelligence and machine learning, in many cases they will still need human help to get the best information from the data. Because there may come a time when computers are smarter than humans in terms of problem solving and speed, but AI cannot learn morality. Even being programmed for it, once machine learning takes over, It is impossible to ensure that you will make the most appropriate decisions. That is why collaboration between human and artificial intelligence will be fundamental. Technology will not replace us, but it will support our ability to make more informed decisions.
– Information at scale to grow the industry: Performance and scalability have always been essential for the success of long-term analytics. Now, with the ability to leverage more data than ever before, relate analytics to operational processes, and bring solutions to more people, the market is “catching up.” More and more solutions offer these capabilities, but companies are also understanding the value of a more holistic approach to data access throughout the organization. In short, companies need more knowledge of the data and that more people have access to the data they need in a flexible way.
Thus, while computers become smarter, so do we: taking advantage of advances in technology we can create more flexible analytical environments. Today we can relate the data and the value of the business, get better visibility about our customers, partners, supply chains and services, create a more aligned alignment between analytics and business processes. All this, if done correctly, will give us more knowledge and competitive advantage.