Data Strategy

Quality data is crucial for automation, pattern recognition, and training AI for advanced capabilities. A data-first mindset and a data-focused platform are essential for long-term success

Meta-data management efforts provide for the management and traceability of all components of the BI environment. Meta-data needs range from ensuring that definitions and business rules associated with BI applications are made available to business users to providing source data mapping information to manage the environment or answer questions rega

The starting point of any RAG system is its source data, often consisting of a vast corpus of text documents, websites, or databases

The cornerstone of a successful RAG implementation is the quality of your data

Also, eliminating irrelevant or sensitive information such as personally identifiable information (PII) is crucial to align with privacy standards

In today’s data world, there are so many options for an EL tool to avoid you developing your own extracting script and to help you gain a LOT of time.

Fivetran, Mage, and Airbyte to mention a few.

You don’t have to maintain custom scripts, these tools come with +300 connectors, basic scheduling, and error handling.

Meta-data management. Meta-data, which is commonly defined as “data about the data” is used to ensure traceability throughout the environment and ensure there is a common understanding of the meaning of the information contained in the BI environment.