Tag: Business Intelligence

Smarter Manufacturing with an Intelligent Data Fabric


As Industry 4.0 continues to transform manufacturing, a sector that was already ripe with information is experiencing a spike in data production from the factory floor to corporate offices. As a result, the market for big data analytics in manufacturing is projected to reach 4.55B by 2026 as the sector continues to adopt “smart industry” initiatives.


While Industry 4.0 poses a tremendous opportunity for manufacturing, the industry faces a number of data challenges – one of the biggest being data silos occurring horizontally and vertically across organizations. This scenario creates a lack of visibility across the organization that can limit productivity and access to key insight needed to influence tasks such as quality assurance, production monitoring, incident analysis, forecasting and competitor intelligence.


Advancements in deep learning and data management are revolutionizing the way the manufacturing industry can harness and operationalize its data. Vyasa has combined these capabilities into its Layar intelligent data fabric. With Layar, manufacturing professionals can connect their data regardless of storage location or file structure. Once connected, Layar applies deep learning on the data sources creating a unified platform without moving or replicating any of the data. This enables content to be easily accessible and searchable allowing users to:

  • Leverage natural language processing to explore their data in a low-code environment.
  • Extract insights from complex documents and images for streamlined quality assurance, incident analysis and more.
  • Improve competitor and customer intelligence by connecting external sources such as websites or social media feeds to internal data.
  • Visualize sensor and production data from the factory floor in intuitive charts and graphs. With an intelligent data fabric, manufacturers can overcome data silos and accelerate their access to data and insights; all while creating a foundation for smart industry initiatives.

With an intelligent data fabric, manufacturers can overcome data silos and accelerate their access to data and insights; all while creating a foundation for smart industry initiatives.


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


Law firm associates spend roughly 35% of their time, or 15 hours per-week, conducting research tasks.1 These tasks are largely conducted online across multiple sources and leveraging various research tools.


Effective research is a critical step of any legal team’s activity – from analyzing cases to identifying laws to determining legal precedent. Collecting these insights requires sifting through large sets of unstructured content, including published reports, legal filings, written case notes and more. Unfortunately, the industry has largely relied on manual processes for conducting this research which is time and labor intensive. As a result, insights are often missed and legal professionals assigned to these tasks often become disengaged or burnout.


Advancements in data management and deep learning are addressing this issue head on. A new data architecture known as the data fabric, enables legal professionals to catalog all of their research data sources in one place, regardless of file format or storage location. The data fabric then acts as an engine for deep learning models to perform text analytics making content easily searchable.

With Vyasa’s Layar data fabric and novel deep learning applications, these capabilities are combined into a single platform enabling legal professionals to:

  • Make data sources accessible across departments. (No need to duplicate your data or storage and no data lake required.)
  • Easily research large sets of documents via natural language question answering.
  • Explore search outcomes via highly-visual applications including knowledge graphs, tables and dashboards.
  • Improve the discovery of novel insights hidden within unstructured content such as reports and case documents.

With Vyasa, legal professionals can improve query accuracy by 97% while decreasing analysis time by 90% leading to more efficient research and smarter legal insights.

1 Lastres, S. Rebooting Legal Research in a Digital Age https://www.lexisnexis.com/documents/pdf/20130806061418_large.pdf


Call center representatives are under immense pressure. They must process large amounts of information and quickly answer questions all while managing caller expectations. In most cases, they’re armed with outdated technology and complicated software which doesn’t make their work easier. No wonder call centers have such a high turnover rate.


To effectively respond to caller requests, representatives typically rely on searching lengthy documents that are in a variety of formats and saved across various locations. Finding the right insights they need is time consuming and in most cases they’re only collecting a small portion of the information available to them. This leads to delays, missed or incorrect information and ultimately, a poor customer experience.


Advancements in data management and deep learning can improve the way call center representatives gather information and serve customers. Through a new data architecture known as the data fabric, Vyasa can unify all data sources available to a call center into a single platform. Deep learning models built by Vyasa can then be applied to the unified data making it easy to search and access in a matter of seconds.

With Vyasa’s Layar data fabric and deep learning applications, call centers can:

  • Make data sources accessible across departments. (No need to duplicate your data or storage and no data lake required.)
  • Quickly search for and access documents in a single location.
  • Query large sets of documents via smart spreadsheets and dynamic knowledge graphs.
  • Discover related concepts and insights with named entity recognition.
  • Extract information into easily shareable file types.

With Vyasa, call center representatives can improve research accuracy by 97% while decreasing analysis time by 90% leading to enhanced call center response and a more positive customer experience.