Data silos impede company operations and the data analytics projects that underpin them. They hinder executives' capacity to use data to manage corporate processes and make sound business decisions. They also prohibit call center agents, sales representatives, and other operational personnel from accessing vital information about customers, products, supply chains, and so on.
“Poor data quality is the unintended consequence of data silos and poor data & analytics governance.”
Source: Gartner
The goal is to combine unstructured, semi-structured, and structured data and make it available as if it were a single database. Kobai’s strategy combines the benefits of data lakes, data warehouses, and cloud-native data catalogues while also including advanced linking methods and text mining capabilities provided by Semantic Graph Technologies.
Understanding Data Silos and Their Impact
Data silos may have technical, organisational, or cultural origins. They tend to emerge naturally in large corporations since various business divisions may operate independently, with their own goals, priorities, and IT budget. Without a well-planned data management strategy, organizations risk creating data silos.
Although data silos could appear innocuous, they hinder departmental collaboration and information exchange. Data quality frequently decreases due to inconsistencies in the data that may overlap across silos. Leaders also find it challenging to have a comprehensive understanding of company data when it is segregated.
Kobai's Approach to Breaking Down Data Barriers
Kobai strives to address the difficult task of combining operational and enterprise data to make better decisions and feedback sophisticated analytics. We provide a next-generation unified platform for integrating, modelling, and visualizing data using AI on an enterprise scale. Our models and ontologies of semantic graph will drive the need to build a connected digital ecosystem throughout the company.
Choosing, connecting, and managing the appropriate tools for managing data, metadata, and analysis is a constantly evolving and often complex task. Our standards-based technology immediately integrates with current data assets to create a reliable, scalable solution. Both technologies provide a solid foundation in semantic graph technology, so data is intuitively related, aligned, and more useful.
Empowering Organizations with Unified Insights
Investing in a semantic data fabric solution opens new opportunities for modern enterprise data management. These are numerous:
- Find, integrate, catalogue, and exchange various types of metadata using semantic data models.
- Make use of text mining: deal with organized and unstructured data simultaneously.
- Graph technologies: do analytics on linked metadata in a semantic graph.
- Use machine learning for (semi-)automated data integration scenarios.
- Automate data orchestration with a powerful data integration backbone.
Other than unifying data silos, here are some other benefits of a semantic knowledge layer:
- Expand your knowledge: You can obtain useful unstructured information about the client on the web, social media, and other sources to help you better understand the customer and the difficulty they are having.
- Predict accurately: Replacement equipment might cost millions of dollars. Anticipating failure to provide life-extending maintenance and preparing for replacement is critical. To accurately predict equipment failure, you must use data from various observation, reporting, and maintenance systems. A data solution that connects text and other data from multiple sources can enhance forecasts and save corporations millions.
- Optimize costs: Not having a complete picture of your employees' abilities and knowledge costs you time and money. Typically, such information is kept separate in HR databases, résumé materials, and other disconnected systems. Combining this unstructured and organized data allows you to save expenses and increase productivity by better matching your employees to challenges and assignments.
Ensuring Scale, Trust, and Readiness for AI/ML
Besides serving as a single source of universal meaning and context for data across the organization, Kobai’s semantic data fabric is also a flexible and reusable set of data services It integrates the organization's on-premise and cloud data sources, providing semantic capabilities for answering complicated queries and facilitating data. Kobai offers the quickest and most convenient development of semantic data fabric coupled to your cloud, on-premise databases, and business intelligence tools.
Drive Your Business into the Future with Kobai
We live in a world where success can be guaranteed because every decision and action can be data-driven. Witness the Kobai difference by leveraging unified data to get strong insights and see your business evolve.
