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TDWI Upside - Where Data Means Business

Looking Ahead: Making Applications More Intelligent and Protecting Sensitive Data in 2020

Building on the work of 2019, these three areas will be key for BI practitioners.

The past year brought several interesting developments as organizations pushed solution providers to increase the intelligence of their applications, data integration, and data management tools and platforms through use of AI techniques.

For Further Reading:

How to Transform a Business with Embedded Analytics

The Broad New Powers of Modern Data Catalogs

Do You Need a Chief Data Governance Officer?

Coming to the end of the year, however, it feels like we are just getting started with these capabilities. I expect that 2020 will bring many initiatives begun in 2019 to much fuller flower. Here are three areas that I anticipate will be key as we move forward.

2020 Trend #1: Embedded BI and analytics will become smarter and more responsive

Not all users have access to (or even want) standalone business intelligence (BI) and analytics tools or web-based services. They do not want to leave their business application or process workflow just to consume or discover data insights. They’d rather do so as part of using their specialized application, business process management, or project management system.

At the same time, demand is rising for these systems to become more data- and analytics-driven. Organizations want systems that use data insights to inform both human decision makers and automated process and decisioning functionality about relevant events and patterns so they can take the appropriate action.

In 2019, we saw increased attention paid to making embedded BI and analytics smarter through an infusion of AI and more data-driven event notification. Both standalone and embedded BI and analytics solutions are incorporating AI functionality that can curate data set selection interaction and offer prescriptive recommendations.

More progress will come in 2020. An inventory manager using a mobile application, for example, will be able to receive smart recommendations in response to data patterns detected in supply chains; field sales personnel can be guided to fuller, contextual information about an important sales prospect.

To prepare for this trend, organizations should identify a particular business process that can be improved with more robust AI and analytics integrated with embedded dashboards, reporting, performance management, or other process applications. Rather than try to “boil the ocean” with widespread changes, organizations should identify a smaller number of processes where the potential business benefits are clear.

2020 Trend #2: Data cataloging, metadata management, and semantic data integration will advance

Knowledge about how data in different systems is defined, its lineage, and how it is related to other data has always been important, but it has been so difficult to achieve that it usually falls well short of being comprehensive or even up to date. As data becomes more distributed across a hybrid, multicloud environment of on-premises and cloud-based data systems, getting a single view of data increasingly depends on a global resource that contains this knowledge.

In recent years, technologies have emerged that provide smart, AI-augmented data catalog and metadata repository development and management. Organizations are becoming better able to give users faster data discovery, self-service access to metadata, and business-driven analysis of data relationships.

Data catalogs, metadata repositories, business glossaries, and emerging semantic integration can help organizations meet many goals. For our forthcoming Best Practices Report (“Faster Insights from Faster Data,” Q1 2020), we asked which goals are most important to organizations with regard to these systems. The one selected by most research participants is making it easier for users to search for and find data (79 percent). The goal with the second-highest percentage is improving governance, security, and regulatory adherence (70 percent). For governance, monitoring access to sensitive data, and data lineage it is essential to know the data’s location, its life cycle in the organization, and how it is being shared.

Organizations should evaluate their current data architecture and BI and analytics platforms to see whether they adequately support their need for comprehensive collection of and access to metadata and other information about the data. Before deploying them widely, organizations should develop proof-of-concept systems with the new technologies to see how well they meet specific needs of users and applications in particular lines of business.

2020 Trend #3: Organizations will integrate governance more effectively with data collection and management

With the European Union’s General Data Protection Regulation (GDPR) and several other data privacy regulations now in full effect -- and with the California Consumer Protection Act (CCPA) due to take effect in January 2020 -- organizations have no choice but to strengthen procedures for protecting customer and consumer data.

Governance is also essential for protecting financial data, intellectual property, and other sensitive information. Governance is not exactly a new trend, but the need for better governance is driving demand for technology solutions and services that use data catalogs and metadata well, can track and monitor data lineage, and can use AI techniques to enable governance across high-volume, varied, and faster data.

Organizations should make sure that key personnel in business and IT understand privacy laws and regulations affecting their customers. Employees on the front lines should be trained in the importance of customer consent to use their data for marketing, sales, and other processes.

Enterprises should apply data integration, management, and metadata technologies that can support governance rules and policies, especially those that use AI techniques to improve speed, accuracy, and scale in locating sensitive data and monitoring how it is used. Effective governance and protection of customers’ data privacy is now a competitive advantage; customers want to do business with organizations that take care of their data.

AI Not Just for the Sake of AI

We expect the excitement about using AI techniques in all things having to do with data will continue to grow but will be tempered by the need to show value. Improving embedded visualization and analytics capabilities in applications and business processes is an important trend in aligning AI capabilities with tangible business benefits.

If organizations can be more efficient and effective with embedded intelligence, they will be confident in expanding AI’s use. Organizations must also ensure that AI use falls within governance, regulatory, and good business practice parameters so customers and business partners are satisfied with new capabilities, not nervous about AI’s impact.

About the Author

David Stodder is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, and related technologies and methods. He is the author of TDWI Best Practices Reports on mobile BI and customer analytics in the age of social media, as well as TDWI Checklist Reports on data discovery and information management. He has chaired TDWI conferences on BI agility and big data analytics. Stodder has provided thought leadership on BI, information management, and IT management for over two decades. He has served as vice president and research director with Ventana Research, and he was the founding chief editor of Intelligent Enterprise, where he served as editorial director for nine years.


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