Enterprise Data Management

Enterprise Data Management

The obstacles that IT faces in providing reliable and timely solutions for data needs across a business are universally accepted and well understood. The challenges associated with the explosive growth and accelerating demands for data from a wide range of users have created a wide range of problems for the business. There is too much data that's too fragmented, redundant, under-utilized, inconsistent, hard to find, hard to understand and growing too fast. This is combined with increasing demands for new products, slick applications, new business models, better customer experiences and compliance to new regulations.

Many projects still fail to deliver quality data to those who need it when they need it. There must be a better way.

We offer data management solutions for departmental as well as enterprise wide needs. Anzo-based solutions provide greater business agility, faster time-to-market and trustworthy data by keeping data relationships and lineage. These solutions use a common conceptual business models to manage data.

FEATURED SOLUTIONS

Data integration is a core part of any information-driven business. Yet, integrating data is often a slow, labor-intensive, and error-prone process that yields incomplete or...

Critical information in any given organization is often buried in free-form text. Whether in documents, Web pages, premiere data feeds like Thomson Reuters or...

Critical information is trapped in Excel spreadsheets on shared drives, in SharePoint, and scattered across laptops. Related data uses different headers, layouts, and...

Service-oriented Architecture (SOA) delivers value to organizations by enabling real-time data integration across disparate systems. As SOA...

Anzo lets both data stewards and business analysts manage concepts, relationships, vocabularies, taxonomies, and thesauri by tracking metadata elements' approval and usage life cycles,. This...

There are lots of tools available for viewing and reporting on data. But options are far more limited when you want to augment, extend or improve existing data with...