Tag: Layar

DON’T MOVE YOUR DATA. UNIFY IT.

Written by vyasa on . Posted in USE CASES.

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.

Problem

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.

Solution

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

TACKLING DATA SILOS POST HEALTHCARE M&A

Written by vyasa on . Posted in USE CASES.

The health services industry is ripe with mergers & acquisitions (M&A). In fact, 2021 deal volumes have exceeded levels from the past three years.1 While healthcare M&A can have significant benefits to patients including access to a larger breadth of services or decreased costs, it often causes major pain points for IT teams tasked with maintaining operational efficiency. Research firm Deloitte notes that IT system integration accounts for 70% of organizational synergies.2

Problem

Healthcare organizations produce and collect mountains of data every day that is subsequently stored in various formats and silos. When healthcare providers merge, IT teams are faced with swamps of data consisting of valuable insight from content such as:

  • Patient records
  • Clinician notes
  • Published research
  • Financial records
  • Medical imagery

Privacy & security protocols as well as interoperability issues make accessing and unifying this data a challenge.

Solution

Advancements in deep learning are revolutionizing the way healthcare organizations can manage, access and extract insights from their most important content. With Vyasa’s Layar data fabric, those in charge of managing data across the healthcare network can unify data sources regardless of file format or where it’s stored and without requiring a data lake. Deep learning models built within Layar automatically catalog the integrated data making it easily accessible.

By leveraging a deep learning data fabric architecture, healthcare organizations can make access to insights a matter of seconds or minutes, instead of days or weeks. Research and analysis is accelerated, as is the accuracy of outcomes, leading to safer clinical trials, improved disease research and a healthier patient population.

1 PwC (2021). Health services deals insights: 2021 midyear outlook https://www.pwc.com/us/en/industries/health-industries/library/health-services-deals-insights.html

2 Deloitte (2018). Health care mergers and acquisitions | The IT factor https://www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/healthcare-it-mergers-and-acquisi- tions-technology.html

MODERNIZING GOVERNMENT DATA INFRASTRUCTURE

Written by vyasa on . Posted in USE CASES.

The impact of the COVID-19 pandemic has spurred innovation in state and local governments. A critical part of these efforts is modernizing IT systems that can support remote operations and collaboration across departments. As municipalities look critically at their current infrastructure, it’s clear that digital transformation will play a key role in years to come.

Problem

As part of the IT modernization process, governments have been undertaking massive projects to digitize records, turning difficult to manage physical documents into unstructured and siloed data sources. These data sources include:

  • Permits & certificates
  • Public health records
  • Court & legal filings
  • Budget forecasts
  • Environmental analysis

While a step in the right direction, this issue doesn’t make records any easier to search or manage. Tackling data accessibility problems will be key to making a more resilient and collaborative government sector a reality.

Solution

A new data architecture is changing the way government IT professionals can approach modernizing their data infrastructure. Known as the data fabric, IT teams can securely unify data sources across departments of government, 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. This makes researching and accessing legal files, public health records, permits and certificates and more a matter of minutes instead of hours or days.

Listed as the #1 strategic technology trend for 2020 by Gartner1, data fabrics are poised to eliminate the need for costly data migrations that can consume budgets and create new data management issues for IT teams.

1 Gartner (2021). Gartner Top Strategic Technology Trends for 2022 https://www.gartner.com/en/information-technology/insights/top-technology-trends

UNIFIED INSIGHTS: ELIMINATING DATA SILOS ACROSS CAMPUS

Written by vyasa on . Posted in USE CASES.

Higher education institutions are rich with data – from results saved by research labs to published content cataloged by libraries to patient records saved by academic medical centers. Each of these data sources are stored at the department level and across various platforms and file formats. As a result, data silos are prevalent across campuses.

Problem

While operating all under the same institution, sharing data and knowledge across departments has become increasingly challenging in higher education. IT teams are tasked with providing infrastructure to meet rising data demands and improve collaboration, while faculty and staff are missing critical insights that can fuel their own research and innovation.

Considering the massive amount of data that is created in higher education each day, this issue will only continue to compound itself.

Solution

A new data architecture is changing the way higher education can manage and share data across departments. Known as the data fabric, IT teams can securely unify data sources across departments, regardless of file format or storage location. 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, content becomes immediately searchable and accessible within a single platform. With Vyasa, higher education institutions can:

  • Make data sources accessible across departments.
  • Enable new ways for researchers to explore their data through highly-visual applications.
  • Improve the discovery of novel insights hidden within unstructured content such as PDFs and images.
  • Reduce time spent on manual research and improve query accuracy.
  • Control system access for secure data sharing across users.

With Vyasa, universities and colleges can overcome data silos, ultimately increasing access to knowledge and improving the quality of research published by the institution.

Unifying Data. Accelerating Insights.

Applications

Layar

Cortex

Synapse

Axon

Signal