Data Democratisation

Strive to make data accessible to everyone in the organisation, regardless of technical expertise. Implement self-service analytics tools, intuitive dashboards, and comprehensive data documentation to empower all stakeholders to make data-driven decisions.

Scalable Data Processing

Set a goal to build a data processing pipeline that can effortlessly handle massive volumes of data without any performance degradation. This could involve leveraging technologies like Apache Spark, Apache Flink, or Google Dataflow to achieve seamless scalability.

Real-Time Analytics

Aim to enable real-time analytics capabilities for the organisation, allowing stakeholders to make decisions based on the most up-to-date information. This could involve building streaming data pipelines, implementing complex event processing systems, and developing real-time dashboards.

Data Security and Compliance

Make it a goal to ensure the highest standards of data security and compliance within the organisation. This could involve implementing robust encryption, access controls, and auditing mechanisms to protect sensitive data and ensure compliance with regulations like GDPR.

Cost Optimisation

Strive to optimise the cost of data infrastructure while maintaining or improving performance. This could involve implementing strategies like resource pooling, dynamic resource allocation, and workload optimisation to minimise infrastructure costs without sacrificing functionality.

Components of the MVC Design Pattern

1. Model The Model component in the MVC (Model-View-Controller) design pattern represents the data and business logic of an application. It is responsible for managing the application’s data, processing business rules, and responding to requests for information from other components, such as the View and the Controller. 2. View Displays the data from the Model … Read more

API Documentation: get_myview

Purpose The get.myview stored procedure API allows Power Applications to interact with the DataWarehouse by performing SELECT queries on specified DataMart views. The results are returned as a JSON array. Security Parameters Required Optional Typical Use URL HTTP Header: cURL Example: PowerBI: PowerShell

Stored Procedure: get.myview

Purpose: The get.myview stored procedure is designed to generate and return a dynamic view of data based on user-defined parameters. It supports complex queries for PowerBI analysis by allowing users to specify various options such as data mart, view name, filtering conditions, and more. Key Features: Example Usage: PowerBI Parameters:DataMart_Host: <DataMart_Host>DataMart_Endpoint: <DataMart_Endpoint>DataMart_Token: <my_token>