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Showing posts with the label An effective methodology for BI Implementation

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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

An effective methodology for BI Implementation

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Given below is an approach that one could follow to ensure an effective implementation of any BI project. Steps in Business Intelligence Project Requirements elicitation is the most important activity in a BI exercise. We need to very clearly understand the motivation behind the management's need for analytics and their short-term, medium-term and long-term objectives.  You may conduct a workshop with all stakeholders to understand these requirements. Identifying and involving all stakeholders in the requirements discussion is very important to gain buy-in for the BI initiative throughout the enterprise. Anyone would like to see a sample of analytics and play around a little to get a sense of the benefit/impact of analytics. Hence developing a quick prototype and showcasing the same to all stakeholders will help you get the necessary impetus for the initiative.  CAVEAT: Please ensure that the prototype development does not take more than two weeks. References Re...