2020 Trends in Data and Business Intelligence
Posted: Wed Jan 29, 2025 5:04 am
Today we have access to more data than we can absorb. But to get the most value, analysis is no longer enough: we need synthesis to bring it all together. In 2020, technology and processes will shift towards comprehensive data solutions that will revolutionize the data ecosystem and drive real change. In this note, we anticipate 10 trends that will help make this possible.
1- Becoming a real-time enterprise is no longer optional. If we are going to make the best possible business decisions, we need our data delivered to the right place at the right time. 5G and IPV6, Kubernetes, streaming architecture, and more can help us respond in an instant and stay ahead of the curve.
2- Big data. With data formats and sources more varied and fragmented than ever before, companies that can achieve synthesis will remain strong.
3- Graph analysis and associative technology will overtake SQL. To tackle larger business problems, you need to move away from row- and column-based queries. Technology that allows you to analyze natural associations within your data will give you better results.
4- DataOps plus self-service improves quality and reduces algeria number data cycle time for data management on the operational side. And self-service minimizes users’ dependency on IT. Together, they help data flow more efficiently throughout the value chain.
5- Active metadata catalogs will be the connective tissue. Demand for data catalogs is skyrocketing as enterprises grapple with massive amounts of data spread across multiple sources. Machine learning catalogs will keep data adaptable and changing, even in hybrid and multi-cloud systems.
6- The emergence of Data Literacy As a Service. The adoption rate of BI tools is currently at 35%. To gain a workforce, companies must develop their data literacy programs, and they are partnering with vendors to make people more comfortable working with their data.
7- Multifaceted interactions will take us beyond search. Technology that can understand and process human expressions combined with tried-and-true data querying approaches is the key to bridging the gap between humans and computers.
8- Ethics and responsible computing are now critical. Technological advances improve our lives, but they can also raise serious concerns. That's why it's more important than ever for companies to ask not just whether something can be done, but whether it should be done.
9- Shazam data. This means that analytics systems can use algorithms to fingerprint our data, find anomalies and insights, and suggest new data to us. If we could “Shazam” our data, analysis and integration would be more efficient and faster.
10- Getting stuck in one data ecosystem will almost always be more expensive in the long run. Independent end-to-end analytics vendors and hybrid/multi-cloud platforms are now a necessity.
Are you interested in learning more about this year's trends?
Download the Qlik eBook to gain broader context, read more in-depth explorations, and see analyst predictions.
1- Becoming a real-time enterprise is no longer optional. If we are going to make the best possible business decisions, we need our data delivered to the right place at the right time. 5G and IPV6, Kubernetes, streaming architecture, and more can help us respond in an instant and stay ahead of the curve.
2- Big data. With data formats and sources more varied and fragmented than ever before, companies that can achieve synthesis will remain strong.
3- Graph analysis and associative technology will overtake SQL. To tackle larger business problems, you need to move away from row- and column-based queries. Technology that allows you to analyze natural associations within your data will give you better results.
4- DataOps plus self-service improves quality and reduces algeria number data cycle time for data management on the operational side. And self-service minimizes users’ dependency on IT. Together, they help data flow more efficiently throughout the value chain.
5- Active metadata catalogs will be the connective tissue. Demand for data catalogs is skyrocketing as enterprises grapple with massive amounts of data spread across multiple sources. Machine learning catalogs will keep data adaptable and changing, even in hybrid and multi-cloud systems.
6- The emergence of Data Literacy As a Service. The adoption rate of BI tools is currently at 35%. To gain a workforce, companies must develop their data literacy programs, and they are partnering with vendors to make people more comfortable working with their data.
7- Multifaceted interactions will take us beyond search. Technology that can understand and process human expressions combined with tried-and-true data querying approaches is the key to bridging the gap between humans and computers.
8- Ethics and responsible computing are now critical. Technological advances improve our lives, but they can also raise serious concerns. That's why it's more important than ever for companies to ask not just whether something can be done, but whether it should be done.
9- Shazam data. This means that analytics systems can use algorithms to fingerprint our data, find anomalies and insights, and suggest new data to us. If we could “Shazam” our data, analysis and integration would be more efficient and faster.
10- Getting stuck in one data ecosystem will almost always be more expensive in the long run. Independent end-to-end analytics vendors and hybrid/multi-cloud platforms are now a necessity.
Are you interested in learning more about this year's trends?
Download the Qlik eBook to gain broader context, read more in-depth explorations, and see analyst predictions.