The Five Most Common Big Data Integration Mistakes To Avoid

whitePaper | February 10, 2022

Modern data governance leaders are searching for the role that governance should play in delivering high-quality data.

whitePaper | June 23, 2021

Analytical data infrastructure (ADI) platforms underpin key analytics models via processes like data integration, preparation, management, and storage. But with complex cloud architectures, as-a-service offerings, and innovative new analytics and process developments, how can the discerning expert choose the right ADI offerings for their business?

whitePaper | June 16, 2022

It seems like the business world has gone crazy for machine learning (ML) and artificial intelligence (AI), viewing the technologies as the essential keys to the very future of the enterprise. In fact, a recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future. And yet, the respondents report that only 25% of AI projects are in widespread deployment and 40% of all projects are generating negative or no returns.

whitePaper | May 5, 2021

Over the last decade, interest in the field of data science has not only increased enormously, but has also changed and developed considerably. In view of the new technological advances and the constant growth of data, we expect Data Science to continue to develop strongly in 2021. We have identified 7 trends that will be relevant for the coming year.

whitePaper | August 19, 2022

Metric Insights recently partnered with Donna Burbank on a webinar on trends for Data & BI governance in 2022. Burbank is the managing director at Global Data Strategy, Ltd., an international information management consulting company that specializes in the alignment of business drivers with data-centric technology.

whitePaper | February 7, 2020

Multiple studies have proven that, while the business demand for databases grows, operational teams are constrained by traditional, reactive processes. Combined with budgetary pressures, this causes them to fall short in meeting the demand in a timely fashion. In addition, as companies adopt cloud paradigms, operational teams must manage across on-premises and cloud environments with the same resources. To be effective, companies need to shift from a reactive posture to one of standardization and proactive analysis and planning by leveraging intuitive tooling to automate manually intensive and non-value adding activities and to deliver real-time insights.