It’s never been easier to share, store and replicate data thanks to our increasingly digital working environments. While this scenario has made activities like collaboration and remote work seamless, the deluge of new data produced within organizations is creating strains on IT systems and resulting headaches for the professionals in charge of managing them. Considering that 64.2ZB1 of data was created or replicated in 2020 alone, it’s no wonder data has not only become the lifeblood, but also the thorn in the side of enterprise IT departments.
Over 80% of organizational data is dark2. IT teams are suffering from dark data if they’re challenged with:
- Multiple data silos
- Redundant or obsolete files
- Unstructured content such as images, PDFs, presentations decks, etc.
Largely inaccessible, yet rich in insight, simply sitting on this data can lead to missed intelligence that can influence product development, sales strategies or competitor research that can drive successful businesses. Tasked with solving this problem, IT teams traditionally turn to unsustainable solutions that require expensive and time consuming data migrations.
A new data architecture is changing the way IT professionals can approach data management. Known as the data fabric, IT teams can unify data sources across their environment, regardless of whether files are stored on premise or in the cloud. No need to duplicate your data or storage and no data lake required.
Vyasa takes this a step further with its Layar deep learning data fabric. Combining the data fabric architecture with novel approaches to deep learning, IT teams that integrate their data within Layar make their content easy to search, explore and visualize, regardless of file format.
Listed as the #1 strategic technology trend for 2020 by Gartner3, data fabrics are poised to eliminate the need for costly data migrations that can impact productivity and create new data management issues for IT teams.
1 Reinsel, D and Rydning, J. (2021). IDC Global DataSphere https://www.idc.com/getdoc.jsp?containerId=IDC_P38353
2 IBM (2015, November 23). The Future of Cognitive Computing. https://www.ibm.com/blogs/cloud0archive/2015/future-of-cognitive-computiving/
3 Gartner (2021). Gartner Top Strategic Technology Trends for 2022 https://www.gartner.com/en/information-technology/insights/top-technology-trends