Data Management

There’s data, and there’s data management. 

Managing your data is about handling all the data portals your organization has to access, integrate, cleanse, govern, store and prepare for analytics. 

Without proper data management, your organization faces numbers it can’t comprehend and is at risk of making poor decisions or feeding insufficient data to automated Machine Learning algorithms that will make wrong decisions. 

Through our Data Management Services, you’ll be able to extract valuable insights from your organization’s data and use them to propel it forward in leaps and bounds. 

Managing your data
  • Data Architecture

    Setting solid foundations for your data is the key to establishing a seamless data management process. That's why it's the first and most crucial step in data management.
    According to The Open Group Architecture Framework (TOGAF), Data Architecture is an offshoot of enterprise architecture that comprises the models, policies, rules, and standards that govern the collection, storage, arrangement, integration, and use of data in organizations.
    Our data architects work with your organization to establish a proper data architecture and enhance it over-time to ensure that it's on par with your organization's goals.

    • Data Access

      You can either spend your time finding data or leverage data accessing systems to allocate different data types from various sources to use them efficiently.

      • Data Integration

        Using data integration tools, you'll be able to combine different data types and either extract, load, and transform them (ELT) or extract, transform, and load them (ETL). Depending on your data integration goals, you'll be able to design and automate the tools to help you consider different data pillars and make better decisions based on the insights you pulled.

        • Data Quality

          If you aren't confident in the authenticity and accuracy of your data, you won't use it. If you decide to use it, you might make some costly mistakes. A data quality tool comes into play here, from the moment the data is accessed until reported; this tool verifies the data in an automated way, increasing your trust in the data and solidifying your decision-making process.

          • Data Governance

            Data governance starts with your organization's policy and strategy regarding managing the data. Using data governance software, you can customize a framework within which you apply regulations, like CECL or the GDPR. Data governance software also helps you track and report how your policies are handled.

            • Business Glossaries, Lineage, and Metadata

              There needs to be a correlation between your business and IT departments. And this is where lineage and metadata (data about data) come in; the glossary will define data and its owners, the lineage will trace the data from its source until the point where it resides, the metadata will help you understand the data further.
              When these three processes are aligned, you'll be able to adopt more of a proactive approach when making business decisions, as the data will give you prolific insights to help you predict and avoid any future hurdles.

              • Data Preparation

                The final step before analyzing the data is to prepare it for analysis.
                Data preparation tools cleanse and filter the data so that only valuable data enters the analytics phase. You can automate this process quickly, and non-tech-savvy employees can access it to tailor the preparation process depending on which data they need to analyze. This process ensures that the analytics results will provide valuable insights, through which you'll be able to make better decisions.