Data Libraries – the Secret Sauce to Regulatory Environments

In this contributed article, Ryan Lougheed, Director, Platform Management at Onspring, discusses how data silos wreak havoc not only on the decision-making process, but also on the ability to enact regulatory compliance. The threat of data duplications and inability to scale are some of the main issues with data silos. And suspect data leads to regulatory compliance issues, like unknowingly not following GDRP regulations, which can lead to fines and other legal complications. Building a comprehensive data library can reap several benefits.

How Data Silos Hinder Big Data Analytics and How to Overcome Them

In this contributed article, IT Professional Subhadip Kumar draws attention to the significant roadblock that data silos present in the realm of Big Data initiatives. In today’s data-driven landscape, the seamless flow and integration of information are paramount for deriving meaningful insights. Unfortunately, data silos pose a formidable challenge to the success of Big Data endeavors.

Survey Finds Improved Access to Siloed, Distributed Data is Financial Tech Executives’ Top Priority for 2022

InterSystems, a creative data technology provider dedicated to helping customers solve the most critical scalability, interoperability, and speed problems, recently sponsored a comprehensive survey of financial services technology executives, exploring how financial firms can use enterprise data to drive actionable insights across their business teams.

insideBIGDATA Guide to How Data Analytics is Transforming Healthcare – Part 3

[Sponsored Post] This technology guide, “insideBIGDATA Guide to How Data Analytics is Transforming Healthcare,” sponsored by Dell Technologies, provides an overview of some of the trends influencing big data in healthcare, the potential benefits, likely challenges, and recommended next steps. If your organization is one of the many that is still in the early stages of implementing its big data analytics strategy, you likely have many questions answered with this new guide.

insideBIGDATA Guide to How Data Analytics is Transforming Healthcare – Part 2

[Sponsored Post] This technology guide, “insideBIGDATA Guide to How Data Analytics is Transforming Healthcare,” sponsored by Dell Technologies, provides an overview of some of the trends influencing big data in healthcare, the potential benefits, likely challenges, and recommended next steps. If your organization is one of the many that is still in the early stages of implementing its big data analytics strategy, you likely have many questions answered with this new guide.

insideBIGDATA Guide to How Data Analytics is Transforming Healthcare

[Sponsored Post] This technology guide, “insideBIGDATA Guide to How Data Analytics is Transforming Healthcare,” sponsored by Dell Technologies, provides an overview of some of the trends influencing big data in healthcare, the potential benefits, likely challenges, and recommended next steps. If your organization is one of the many that is still in the early stages of implementing its big data analytics strategy, you likely have many questions answered with this new guide.

insideBIGDATA Guide to How Data Analytics is Transforming Healthcare

This technology guide, “insideBIGDATA Guide to How Data Analytics is Transforming Healthcare,” sponsored by Dell Technologies, provides  an overview of some of the trends influencing big data in healthcare, the potential benefits, likely challenges, and recommended next steps.

The Data Silos Holding You Back are All in Your Head

In this contributed article, Pete Goddard, CEO and co-founder of Deephaven Data Labs, paints a new picture of data: one of a synchronized group effort rather than a relay race of individual, siloed teams. He explains how the “baton pass” method of working with data – inherently full of risks and slow-downs – has evolved but not quite met the needs of modern data teams. Pete then outlines how de-compartmentalizing data use cases can lead to a new understanding that data is changing and exists on a continuum of time. When all data problems are viewed through the lens of how data needs to meet software, and diverse teams are brought together to work in tandem on these interesting problems, we can create one frictionless data world free from the current limits of intermediation.