Effectively managing data privacy and security is a high-stakes matter. When an organization doesn’t get it right, it often becomes front-page news and occasionally becomes a subject of litigation. Yet organizations face an equally challenging imperative to ensure that business users have easy access to the data they need. Depending on how they are implemented, data governance policies can inhibit access to data, making it harder to find and utilize the data assets of an organization.
I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.
Ventana Research recently announced its 2020 research agenda for data, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value and improve business outcomes. Data volumes continue to grow while data latency requirements continue to shrink. Meanwhile, virtually every organization is confronting a need for good data governance.
Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.
Qonnections 2019 is Qlik's annual user conference. Key news from this year's conference centered on acquisitions of Podium Data and Attunity, along with an expansion of certifications on Google Cloud Platform, AWS, and Azure, with the ability to support Red Hat OpenShift. Many of these announcements were centered on a key theme of a cloud and SaaS-first approach.
Organizations now must store, process and use data of significantly greater volume and variety than in the past. These factors plus the velocity of data today — the unrelentingly rapid rate at which it is generated, both in enterprise systems and on the internet — add to the challenge of getting the data into a form that can be used for business tasks.
This year, Teradata rebranded the Teradata users conference from "Partners" to "Analytics Universe", and there is a reason for it. For decades, Teradata has represented the high end of the analytic database, but new innovations and technologies are adding flexibility to Teradata's licensing as they compete. For the full breakdown of Teradata's Analytics Universe 2018, and my analysis of all the largest announcements, watch my hot take video.
We at Ventana Research recently published our research agendas for 2018. The world of data and information management continues to evolve, as does our research on the use of these technologies to improve your organization’s operations. Relational databases are no longer the only viable enterprise data store as more organizations adopt a polyglot database infrastructure. And while their exact form may still be changing, as I have recently written, big data technologies are here to stay. Our Data and Analytics in the Cloud Benchmark Research indicates that an increasing number of organizations are opting for cloud-based deployments: A modern data infrastructure includes a hybrid of on-premises and cloud deployments for 44 percent of organizations. Our upcoming research will track how these changes are affecting data- and information-management processes.
Big data has become an integral part of information management. Nearly all organizations have some need to access big data sources and produce actionable information for decision-makers. Recognizing this connection, we merged these two topics when we put together our recently published research agendas for 2017. As we plan our research, we focus on current technologies and how they can be used to improve an organization’s performance. We then share those results with our readers.
Topics: Big Data, Data Science, Analytics, Data Governance, Data Integration, Data Preparation, Information Management, Internet of Things, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
The business intelligence market is bounded on one side by big data and on the other side by data preparation. That is, to maximize their performance in using information, organizations have to collect and analyze ever increasing volumes of data while the tools available are constantly evolving in the big data ecosystem that I have written about. In our benchmark research on big data analytics, half (51%) of organizations said they want to access big data using their existing BI tools. At the same time, as I have noted, end users are demanding self-service access to data preparation capabilities to facilitate their analyses.