Precision-DM - Consulting
Brief descriptions are given for each of the consulting topics below. If you are interested in any of these, please let us know your interest.
Note: With the current pandemic situation, all consultations can be conducted online.
Data Audits | Short 2-3 week arrangements to look into, assess and report potential gaps and recommend possible improvements with regard to any aspect of your data ecosystem. |
Data Strategy | A data strategy helps to show where projects are going, how they are aligned to overall company objectives and how the individual projects and activities are related to each other. It is important that a Data Strategy be developed as early as possible. |
Data Governance | Data governance is about the control framework that needs to be put in place to ensure that the data projects that you do are successful and sustainable. Data governance brings together the policies, processes and the people aspects that will be required to ensure that the technology supports the business goals of your organisation. With proper data governance, the impact of data projects will be short term. |
Data Quality Metrics | Data quality metrics is about measuring the quality of data types that you consider important to your business and displaying the results in a dashboard. Although the idea of measuring quality is not new, the practical implementation of metrics is. Data quality metrics in a dashboard provides the transparency that is crucial for the organisation, especially Management, to be able to see the actual condition of data, not what the condition is speculated to be. |
Data Science Requirements | There is a high level of interest in applying data science and machine learning to data in the hope of revealing new insights. But just throwing technology on top of data, good and bad is dangerous and can damage your business. This consulting topic helps you understand the condition your data needs to be in prior to applying data science. |
People Skills Development | It would be difficult to properly run a data management program without skilled and competent staff to drive it, This can be addressed either through formal courses or coaching and mentoring which we also provide. But it should start with an assesment of your people so that an optimal plan can be developed. |
Data Architecture | Organisations typically have a team to look at systems architecture and very often, it is assumed by the architecture team as well as everyone else that their work covers data architecture. This can lead to problems for the data management team if the data architecture is sub-optimal. Understanding how to translate what you want to achieve for your data projects and how to map that into your data achitecture and communicate with the architecture team is key to having an effective data architecture. |
Data Management Portfolio Management | Portfolio management typically refers to the management of all assets within the portfolio. In the area of data, this has still not been clearly defined and is somewhat open ended. It can be simply the databases, systems and applications specifically used for managing data. Or it could be expanded to also include processes, dataflows, business rules and people. How you define it will depend on several factors some of which include your organisation's long term strategy, your data strategy, team structure and skilsets as well as your customer base. |