Data Management Services

Osprey helps clients optimise business processes for maximum efficiency and galvanise their IT infrastructure to be both resilient and robust. Osprey offers the following solutions:

  • Data Management Services
  • Data and Information Governance

Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.

The data management process includes a combination of different functions that collectively aim to make sure that the data in corporate systems is accurate, available and accessible. Most of the required work is done by IT and data management teams, but business users typically also participate in some parts of the process to ensure that the data meets their needs and to get them on board with policies governing its use.

Osprey’s comprehensive guide to data management further explains what it is and provides insight on the individual disciplines it includes, best practices for managing data, challenges that organizations face and the business benefits of a successful data management strategy.

Importance of data management

Data increasingly is seen as a corporate asset that can be used to make more-informed business decisions, improve marketing campaigns, optimize business operations and reduce costs, all with the goal of increasing revenue and profits. But a lack of proper data management can saddle organizations with incompatible data silos, inconsistent data sets and data quality problems that limit their ability to run business intelligence (BI) and analytics applications — or, worse, lead to faulty findings.

Data management has also grown in importance as businesses are subjected to data governance an increasing number of regulatory compliance requirements, including data privacy and protection laws such as GDPR and the California Consumer Privacy Act. In addition, companies are capturing ever-larger volumes of data and a wider variety of data types, both hallmarks of the big data systems many have deployed. Without good data management, such environments can become unwieldy and hard to navigate.

We help organisations develop their Data Management Strategy
the overall data management process includes but not limited to cover a series of steps, from data processing and storage to governance of how data is formatted and used in operational and analytical systems.

Development of a data architecture is often the first step, particularly in large organizations with lots of data to manage.

Osprey’s Data management Strategy involves a variety of interrelated functions.

Osprey’s Data management Strategy involves a variety of interrelated functions.
Osprey’s fundamental data management disciplines include data modeling, which diagrams the relationships between data elements and how data flows through systems; data integration, which combines data from different data sources for operational and analytical uses; data governance, which sets policies and standards to ensure data is consistent throughout an organization; and data quality management, which aims to fix data errors and inconsistencies. Another is master data management (MDM), which creates a common set of reference data on things like customers and products.

Data management best practices

A Osprey’s well-designed data governance program is a critical component of effective data management strategies, especially in organizations with distributed data environments that include a diverse set of systems. A strong focus on data quality is also a must. In both cases, though, IT and data management teams can’t go it alone. Business executives and users have to be involved to make sure their data needs are met and data quality problems aren’t perpetuated.

Data management risks and challenges

If an organization doesn’t have a well-designed data architecture, it can end up with siloed systems that are hard to integrate and manage in a coordinated way

Many data management teams are now among the employees who are accountable for protecting corporate data security and limiting potential legal liabilities for data breaches or misuse of data. Data managers need to help ensure compliance with both government and industry regulations on data security, privacy and usage. That has become a more pressing concern with the passage of GDPR, the European Union’s data privacy law that took effect in May 2018, and the California Consumer Privacy Act, which was signed into law in 2018 and is scheduled to become effective at the start of 2020.

Benefits of good data management

A well-executed data management strategy can help companies gain potential competitive advantages over their business rivals, both by improving operational effectiveness and enabling better decision-making. Organizations with well-managed data can also become more agile, making it possible to spot market trends and move to take advantage of new business opportunities more quickly.

Effective data management can also help companies avoid data breaches, data privacy issues and regulatory compliance problems that could damage their reputation, add unexpected costs and put them in legal jeopardy. Ultimately, the biggest benefit that a solid approach to data management can provide is better business performance.