Bratislava, Prague, January 20, 2022 – In today’s world, success requires cooperation – not only with colleagues, but also with suppliers, customers and even the competition. What role does data play in the path to success? Take a look at the top 10 trends in working with data for 2022 according to the technology company Qlik and find out how to use them to your advantage. So, what are the key BI trends that will take the business world by storm in 2022? Read on…
1. Collaboration mining arrives
The shift to work-from-home made it critical to embed BI within workstreams and apps. But collaboration after insights are found is just one piece of the puzzle. Working together has to begin earlier, as part of the initial analytics workflow. And going forward, just as you mine data, you’ll have to learn how to “data-collaboration-mine,” too, so that you can immediately turn the results into decisions or actions.
Therefore, in addition to data mining, the attention will have to paid to collaboration mining, too. We will take a closer look at its mechanics to improve the way we connect data, networks and processes. In other words, just as we have learned to obtain data and processes, we will see the onset of “collaboration mining.” This will make it possible to monitor decisions, address key audit matters and strengthen stakeholder’s confidence.
What analysts say: “By 2023, up to 30% of organizations will use the collective intelligence within their business, thus outperforming the competition that would still rely solely on centralized analytics and self-service analyses.“ — Gartner
2. The dashboard is dead. Long live the dashboard.
You hear a lot about the end of the dashboard – but deep analysis within interactive applications is here to stay. There is a big difference between simple tracking of KPIs and in-depth, investigative analyzes, which rely on rich, interactive and advanced analytics. So how is the data dashboard evolving? It’s becoming highly contextualized with AI and alerting. And it’s becoming highly collaborative, maturing into a hub that catalogues insights and distributed data
The analyses will continue to shift from a passive approach (i.e. waiting for results) to a more active one, where analyses are the engine that dictates the direction and rhythm of business. Analyses will become increasingly contextual and collaborative, capable of an immediate and sophisticated response to a change in data. This is mainly due to the increasingly advanced AI (augmented intelligence in this context) technologies which complement processes and help them step in the right direction.
What analysts say: “As advanced analytics and BI will become available to a wider range of end users, BI will penetrate 50% of businesses for the first time, thus influencing even more processes and decisions “ — Gartner
3. Data lineage provides explainable BI
Analytics users often struggle to explain their data, and fragmentation has made the problem worse. But today, distributed architectures are emerging, with augmented metadata that includes lineage.
In an intertwined world, lineage will be mission-critical to providing trust and “explainability“. Today’s world ravaged by hoaxes and half-truths shows how important high-quality, reliable and verifiable data are.
What analysts say: “By 2023, organizations with common ontology, semantics and management processes will perform better than those that chose not to unify their processes.“ —Gartner
4. Insight velocity brings cost into focus
Live-querying cloud data repositories is a great tool for discovery. But cloud-compute costs can skyrocket. In the long term, insight velocity and cost-per-insight will increase, and you’ll have to figure out how to run the right queries in the right place.
What analysts say: „ By 2023, 50% of public cloud clients will experience cost increases and project failures caused by poor management.“ — Gartner
5. Distributed clouds emerge
Specialized workloads exist for a reason: Processing can be faster at the edge. Compliance is critical. And security is more important than ever. A distributed cloud infrastructure may feel messy, but it strengthens your ability to both access and share interwoven data securely and confidently.
What analysts say: “In 2025, about 50% of large enterprises will implement transformational business models that use distributed cloud services in any location.“ — Gartner
6. Embedded insights become pervasive
To build a collaborative, outside-in approach to innovation, you need to open up your analytics to your partners, customers, and broader ecosystem – and embed them at every link in the chain. However, it is not just about embedding analytics applications or dashboards in non-analytical systems. In particular, it involves embedding a system of alerts regarding “micro-insights” that may help reach a decision. When contextualized micro-insights are more pervasive, it will increase trust in the system.
What analysts say: “By 2022, more than one-half of line-of-business personnel will have immediate access to cross-functional analytics embedded in their activities and processes, helping to make operation decision-making more efficient and effective.“ — Ventana Research
7. Application automation triggers action
The API economy opens up new ways to interweave in joint initiatives with your partners. And app automation is a strongly emerging area that removes the need to code these integrations, making the opportunity more accessible to a wider variety of participants. By doing so, you can use analytics with low-code AI or machine learning, which until recently seemed like a well-written sci-fi.
What analysts say: “By 2023, 60% of organizations will use three or more analytics systems to create a network of decision-making applications that link insights to specific actions.“ — Gartner
8. Data science overlapping with analytics upskills everyone
Data science has been seen as something only the few can do. But if common predictive use cases become more accessible for regular users – and if they include explainability and governance – data science, overlapping with analytics, will enable more people to do more.
What analysts say: “The shortage of data scientists in 2025 will no longer be an obstacle to the introduction of data science and machine learning in organizations.“ — Gartner
9. Security becomes a top priority
Regulations are now conflating data management, privacy, security, and identity and access management. And the more you share APIs and data, the more you need to protect against failures. Does this mean that the pursuit of data safety will hamper our progress? Not necessarily. Technologies and methodologies are becoming more advanced and safer. As you interweave with partners, protections shift from nice-to-haves, to musts, to business opportunities
What analysts say: “By 2025, 80% of organizations working to expand their digital business will fail because they lack a modern approach to data and analytics management.“ — Gartner
10. Data Mesh becomes the new fabric for distributed data
The need for faster access to data across increasingly distributed landscapes is driving integrated data management that uses metadata, semantics, real-time and event-driven data movement, and orchestration in the pipeline. Putting these capabilities into a distributed architecture is being referred to as a “data fabric.” The discussion on how to handle distributed data has evolved into “data mesh”.
What analysts say: “Organizations that use active metadata to enrich and deliver dynamic data fabric will reduce the time required for integrated data delivery by 50% and increase data team productivity by 20% by 2024.“ — Gartner
