Business Insights on Azure: 1-wk Assessment

Dimension Data

Assess your data to understand the hidden information stored within your Azure and hybrid environment. Design new metrics to drive your organisation in a digital world.

A consultative process defines our Business Insights Assessment using a methodology grown in our Digital Advisory services.

Traditional metrics do not always provide all the information required to steer an organisation in the fast-paced digital era. Our data science capabilities will enable you to understand what information your data holds, so that you can act upon it, allowing for transformation and innovation. By combining an experienced team of data engineers, data scientists, mathematicians and business analysts, with a fit for purpose, and robust data science process, we offer a complete end-to-end solution to find, shape and deploy informational flows to solve your business challenges using the power of your data stored in Azure or in your hybrid environment.

A workshop is held with business stakeholders, analysts and architects with the following agenda:

  1. Defining objectives: understand and identify the business problems,and define the business goals to be unpacked by the data science methodology

  2. Identify data sources within your Azure and/or hybrid environment: Find the relevant data sources which hold the information to address the objectives of the project;

  3. Define Project Success: One of the key elements derived in the Business Insights assessment is ensuring that there is a clearly defined and articulated metric or metrics as the measure of success. This formula will be designed and articulated by our mathematicians and data scientists for your organisation.

Assessment Outcomes:

  1. Documented business requirements; functional documents for data science techniques to target;
  2. A clearly defined and articulated metric or metrics that will act as the measure of success;
  3. Identification and outlining of resources for a potential project post assessment i.e. data sources, system requirements and domain experts from Business;
  4. Definition of the project team and iteration milestones in a plan for a potential analytics project.