Nogamy Pro
End-to-End projects in all Data Analytic domains
ArrayThis service is designed to build an array of
BI \ Data Analytics \ BigData \ AI
via a project methodology, fully managed and accounted for by Nogamy.
We carry out a wide range of projects. After studying your organization’s needs, we will identify which components of a Data Analytics solution you are missing and, in accordance, offer an implementation project. The project will be carried out from A to Z with full Nogamy accountability – starting from initial gathering of requirements to implementing the solution and providing maintenance & support.
Step 1: Understanding the need and gathering the requirements
- Defining data requirements by conducting meetings with key stakeholders in the organization.
- Defining needs for data analysis, reporting, performance metrics.
Step 1: Understanding the need and gathering the requirements
- Defining data requirements by conducting meetings with key stakeholders in the organization. - Defining needs for data analysis, reporting, performance metrics.
Step 2: Solution High Level Design
- Recommendation for the best-fit technological tools.
- Architecture plan for a Data Analytics array.
- Design logical data model of Facts & Dimensions.
- Phased Work Plan to implement the recommended solution.
Step 2: Solution High Level Design
- Recommendation for the best-fit technological tools. - Architecture plan for a Data Analytics array. - Design logical data model of Facts & Dimensions. - Phased Work Plan to implement the recommended solution.
Step 3: Data Analysis
- Understanding the business rules of the content domain.
- Performing information analysis against the data sources.
Step 3: Data Analysis
- Understanding the business rules of the content domain. - Performing information analysis against the data sources.
Step 4: Detail Design
- Detail Design of the Measures, Facts and Dimensions.
- Technical Design of the DataHub layer.
- Detail Design of the Data Model
- Visualization layer design - planning dashboard functional flow, business question layout, and the relevant visual objects.
Step 4: Detail Design
- Detail Design of the Measures, Facts and Dimensions. - Technical Design of the DataHub layer. - Detail Design of the Data Model - Visualization layer design - planning dashboard functional flow, business question layout, and the relevant visual objects.
Step 5: Development
- DataHub and data integration from data sources (ETL)
- The Semantic Layer and dashboard screens in the BI application
- During the development phase, intermediate deliverables will be presented to business users in order to receive feedback and make adjustments
Step 5: Development
- DataHub and data integration from data sources (ETL) - The Semantic Layer and dashboard screens in the BI application - During the development phase, intermediate deliverables will be presented to business users in order to receive feedback and make adjustments
Step 6: Quality Assurance
- Tests for data accuracy and consistency at the visualization layer.
- Functional tests of all presentation layer objects and of the integration between them.
- Performance and response time tests.
Step 6: Quality Assurance
- Tests for data accuracy and consistency at the visualization layer. - Functional tests of all presentation layer objects and of the integration between them. - Performance and response time tests.
Step 7: Deployment
- User training.
- Technical and practical training for IT people
- Delivery of training material, including term & definition dictionary
Step 7: Deployment
- User training. - Technical and practical training for IT people - Delivery of training material, including term & definition dictionary