Enterprise Information Management
Aarisha provides Enterprise Information Management, both on-premises and for cloud services, offering the only complete solution for Enterprise Information Management offering a comprehensive view of all the information within the organization
Enterprise Information Management (EIM) solutions manage the creation, capture, use and eventual lifecycle of structured and unstructured information. Aarisha's EIM solutions are designed to help organizations extract value from their information, secure that information, and meet the growing list of compliance requirements.
Aarisha's Enterprise Information Management Software platform manages and analyzes information, enabling the Intelligent and Connected Enterprise with machines (automation), artificial intelligence (AI), Application Programming Interfaces (APIs) and data management combined into an intelligent information core. Information from humans and machines are brought together and securely managed, stored, accessed and mined, with analytics, for actionable insights.
Aarisha follows the unstructured content, ranging from customer information and case files to employee information, transactions and interactions along the supply chain to information used to manage assets, such as planes, trains, automobiles, nuclear power plants, oil rigs, to industry accelerators, such as IT and innovation platforms.
Aarisha's experts encourage you to house your enterprises data in a more structured form that provides overall support for analytics, managed data cleansing, enrichment and integration, and compliments other architecture like a data lake and big data.
Data strategy and planning : Lays the foundation for a new data warehouse or a plan to improve the existing one.
Data warehouse consulting : Customized workshops and assessments to design a high-performant Azure Data Management solution.
Data integration services : Integrate data from an on-premise and cloud source system into Azure SQL Data Warehouse.
Data reconciliation : Execute end-to-end testing to validate and reconcile between source and target system.
ETL : Extract, transform, and load (ETL) legacy data into a cloud data warehouse.
Data warehouse analysis : Business requirements gathered to convert the data warehouse into a scalable data structure.
Aarisha's Cloud Data Lakes integrate data from disparate sources, govern data quality and deliver a single version of the truth. With data privacy and security built in from the ground up, these "little-engines-that-could" also deliver cloud-enabled scalability, self-service capability for democratized access, and faster time-to-market for new data products.
Aarisha's Cloud Data Lakes services come with our incisive knowledge and expertise to support your business in deciphering these central questions before driving the cloud engineering behind your eventual storage architecture. Aarisha's Cloud Data Lakes consultants meticulously evaluate your enterprise's specific data formats, sources (raw vs. structured), end users, processing requirements, and intended outcomes. The goal is to address pain points within your current data storage infrastructure that can be resolved within these new, more efficient frameworks.
- Well-organized, accessible Data Lakes for large volumes of raw data for use in myriad future analytics applications, primarily managed by data scientists.
- Data Warehouse architecture that comprises structured, filtered data ready for analytics, giving business users multiple self-service options for analytics, data visualization and reporting applications.
- A combination of Data Lakes and Data Warehouse architecture, with appropriate hierarchies, security, and governance rules providing a best-of-both-worlds solution.
Aarisha specializes in building native data lakes that power faster, cheaper and more agile cloud analytics for IT, business users and data scientists.