Rapid technological advancements have enabled businesses to access large volumes of data flowing in through multiple touch points across the network. However, without the capability to collate, structure, and analyze data, it remains unusable. A unified data storage and analytics system can facilitate data-driven decision-making based on actionable insights. VisionTree partners with customers to create Data Lake across lines of business and consolidated ones for stakeholders both for structured and unstructured data.
Many organizations do not have Big Data. They load their RDBMS content only and expect them to provide business insights. Enterprise data today is both transactional and unstructured, publicly available and privately collected, and its value derived from the ability to aggregate and analyze it.
VisionTree creates either Data Lake, Data Warehouse, or Data Mart for its customers where data sets isolated into Data Repository from several application databases; they are classified and tagged with metadata for a better data structure which later on used for data analysis, sharing, and reporting purpose.
Additionally, we develop role-based access rules to allow only authorized users with a legitimate business need to access, modify, or transmit data as per the segregation of duties.
The idea of a fabric connecting computing resources and providing centralized access has been around since the early concepts of grid computing; however, integrating data is a persistent problem. Enterprises need to bring together data from transactional data stores, data warehouses, data lakes, machine logs, unstructured data sources, application storage, social media storage, and cloud storage.
VisionTree partners with customer to create big data fabric that provides seamless, real-time integration and access across the multiple data silos of a big data system through Hadoop clusters and SAP Vora by establishing Data hierarchies for better correlation across Hadoop and operational data.
Many enterprises have realized that the data they own and use it can make them different than others to innovate, to compete better and to stay in business. Hence organizations try to collect, process and transform them as much possible for meaningful information with data-driven discoveries and deliver in the right format for smarter decision-making.
VisionTree deploys data scientist and developers to prepare data models, data assets catalog, data workflows, user-based authorization access and metadata structure readiness for big-data analytics.
In order to derive effective data insights, VisionTree partner with customer for broader Master Data governance strategy that addresses analytics need of every mission-critical line of business.
Whenever any enterprise decides to create their data lake, they also must plan to prevent undesired access to their environment by protecting your data lake property, whether it is on-premise or in the cloud. Additionally, the enterprise needs to secure platform access, and platform privilege to store data, execute jobs, tools to manage the system and the repositories.
VisionTree partners with the customer to apply the data encryption at the storage level as well as network level where data travels for stronger data protection. We additionally implement document permission sets, and content permission sets data sets stored in a data lake for enterprise search.
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