Legacy data management solutions have not delivered the connected data ecosystem they promised. In fact, the proliferation of SaaS applications, data warehouses, and data lakes has even further decentralized data, making it difficult for anyone to find, access, and use. Data fabrics offer a new path forward, and it looks quite different from the rows and columns we were once used to.
What results can a data fabric really achieve? See for yourself.
Read how the largest wine and spirits distributor in the US leveraged DataOS to optimize sales and marketing operations and to increase the value of their advertising inventory. Within six weeks, Modern Data helped establish a single source of data, centralized governance, data discovery, real-time data and processing, and the ability to securely syndicate.Download
Healthcare organizations face the constant challenge of improving operational efficiency and maintaining the highest standards of patient care. From aging and growing populations to the expanding prevalence of chronic diseases and rapid, but costly, innovations in tools and tech—these are just a few of the developments that are increasing care demand and cost.Download
Supply chains are complex webs that are composed of people, products, and processes. When governed by bad data strategy, each component functions as a siloed node in a linear system operating in a relay. When disasters hit one node, entire systems across the globe can crumble.Download
As you already know, the enterprise data landscape is increasingly varied and always changing. Traditional data management solutions simply can't keep up with the growth of IoT, rise in unstructured data volume, increasing relevance of external data sources, and trend towards multi-cloud environments. Today’s use cases don't fit neatly into data models where data is related in rows and columns. Instead, they require a model that is smart, flexible, and scalable.
Data fabrics offer a simple answer. A data fabric is a data architecture and set of data services that weave together data from internal and external sources to create a reliable source of information for your business applications, AI, and analytics. Given its approach, data fabrics are not a rip and replace solution. Data fabrics, including DataOS simply stitch together what you already have, supporting the full breadth of your complex data needs.