WITSIDE's Effort Estimation Service is an end-to-end methodology that accelerates the process of getting start on Azure by providing a safe and solid estimation of the relevant effort.
WITSIDE's Effort Estimation Service is a 2 weeks Assessment supported by an application, in order to estimate the effort required to implement a Data Analytics/AI Project on AZURE. WITSIDE’s Effort Estimation Service accelerates the process of getting start on Azure because provides a safe and solid estimation of the relevant effort, thus its’s easier for the end customer to start his journey, utilizing all the technology advantages of Data & AI in Azure stack, plus the flexibility of Azure infrastructure and the option to scale as going forward, with zero maintenance cost. The Service utilizes users’ input on several parameters (i.e., type of analytics project, scope, success KPIs, data volume, technology to use, client digital and data maturity, location/market, limitations, etc.) as well as industry benchmarking data. Occasionally, expert opinion and consultation with the Client might be also required to provide the best possible estimates, based on the information shared.
Who is this for? WITSIDE’s Effort estimation Service can be used by service providers, integrators or /and internal teams for effortless data analytics project on AZURE sizing.
How does this work? WITSIDE's Effort Estimation Service uses Functional Point Analysis (FPA), a software sizing methodology that is used to measure the functional requirements & complexity of a software project in terms of cost and effort.
The excess WITSIDE differentiation FPA involves identifying and categorizing the different types of functionalities provided by the solution and assigning weights to them based on their complexity and significance. FPs are derived using an empirical relationship based on countable measures of solution’s information domain and qualitative assessments of solution's complexity. It is based on the functionality provided by the solution, such as input, output, queries, and user interactions. However, WITSIDE adjusts the corresponding weight categories in order to match more specific project related measures, integrating at the same point AZURE platform capabilities and features. Once the weights have been assigned, the project’s total number of function points is calculated. WITSIDE also uses structured questionnaires to assess analytics maturity, data quality, data volume and frequency of updates and gather some basic information, such as problem definition, departments, roles and number of users involved, existing process, expected outcome, success criteria and existing technologies/applications. After processing the data and reviewing the information, a focused 2-hour workshop will follow with the sponsor, business owner, IT and key users of the client, who will provide further details by replying in semi-structured questions, such as objectives per stakeholder, challenges with the current process, existing IT landscape, potential limitations to consider, ETL and data flow monitoring procedures, as well as operations and maintenance issues. By processing the above information, the Effort Estimator provides the Estimated Effort report, along with the relevant working assumptions. By changing any of the parameters in the answer, the effort will be re-calculated and an updated report will be provided.
Deliverables: Total project effort and fee estimates (range), breakdown per work package (if provided) and projected timeline, along with the main working assumptions in order to ensure a successful Data Analytics project on AZURE.