Break down your data silos. Democratize your data with a single view of disparate data.
Do you store your data in several databases, in many formats, across different platforms? Are you struggling with the stringent needs of data integration and facing challenges with business agility? Data Virtualization integrates all the data from disparate sources into a virtualized layer without moving the data. Traditional central data stores like data marts, warehouses, and data lakes are costly and time-consuming when dealing with many data sources at speed. With data virtualization, you can accelerate your time to value with faster and accurate queries.
A virtual data layer without moving the data to a physical data repository. Data retrieved from multiple sub-queries via the data ingestion layer created for a composite data view to be made available for all the business applications.
Establish connection to any data source, combine data from any format (NoSQL, Hadoop, RDBMS, and excel files), to generate your insights (dashboards, reports, mobile apps) in an agile manner.
Data virtualization is about a federated and distributed query engine to search, discover and govern the data and relationships.
Connecting to data is superior to collecting it with data virtualization services. It delivers holistic real-time data to all the business applications across the organization.
No more data silos. Access your data from a single point to explore your data faster and with efficiency.
Enable real-time data access and insights without data movement, duplication, ETL processes, or storage requirements.
With data virtualization, you can cut down your migration and duplication costs. You can democratize your data access and improve governance and security.
Data available in real-time with self-service access for all the business users. You can query across different databases and big data repositories with centralized control. Queries powered by Machine learning to accelerate your time to value.
InsightBox is designed to address your organization’s data needs, connecting any data sources and translating them to an organized data environment, better visualization, prediction, and decision-making. Industry and function-specific library of reports/dashboards help you get started with your dashboard in just a day.
Efficiency at the nucleus, this platform is designed to reduce time to data, increase data visibility and facilitate better decision making.
EMR, and EHR gained wide popularity in the healthcare system. It is not just them, but patients today prefer self-service from their healthcare providers, and wearables also became part of everyone’s life. All this is leading to more heterogeneous data with a variety of sources and formats. Insurance claims and treatment plans now depend on the lifestyle and medication adherence of the individuals. So healthcare providers and payers need a centralized virtual repository like data virtualization that can generate insights from these disparate data sources
Financial services firms these days must act fast to identify fraudulent and non-compliance transactions. A real-time view of the customers, their transactional insights, credit scores, and personal information – all from many sources need to be centralized to understand the holistic view of the customers. Data virtualization at the core of the architecture enables seamless real-time insights, timely transactional intelligence, and centralized security and governance for financial institutions.
Machines today generate most of the data in the world. With the latest technologies like IoT, Cloud computing, machine learning, and big data, the manufacturing industry is poised for more process efficiencies. The sensors from the equipment/machines today give a large amount of data that can be leveraged to predict equipment maintenance, failure, and sensitive conditions. The modern manufacturing value chain involves a large gamut of data from highly structured to semi-structured to unstructured data. Data virtualization can help connect these wide varieties of data in a single source of truth for the manufacturing process, thereby enabling insights to streamline the processes for quality and efficiencies.
Retail business is changing every day, and they are trying to understand customers effectively to offer more personalized products/services. Big data, analytics, artificial intelligence, social media analytics, real-time insights are among the few investments by retailers in the recent past. Despite all this, they want to understand their customer very fast, aggregating many data sources. Retailers can create a centralized view of the customers, products, suppliers, social media, and logistics, leveraging data virtualization in a few weeks.
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