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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...
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New Directions for Digital Products (1 of 2)

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We already crossed Agriculture, Industrial, Information age. Now we are in digitization age. Many companies investing huge money in digitization.
digital technologies
  • Mphasis - is betting on the digitization of Financial institutions
  • Tech Mahindra - started research on Heath care digitization
  • Infosys - focusing on Automation and artificial intelligence
  • TCS - focussing on Machine learning
  • WIPRO - is focusing on Big data and Hadoop

What is digitization

  • What we mean by digital. Digital data is distinguished from analog data in that the datum is represented in discrete, discontinuous values, rather than the continuous, wavelike values of analog. Thus, the digitization of data refers to the conversion of information into binary code, allowing for more efficient transmission and storage of data.
  • A key differentiator of our current age from prior human history is that, as of the last decade, we not only convert data to a digital format, but we also create data in a digital format. Thus, we now have the digital product, a concept defined by Scupola (2005) as "a product whose complete value chain can be implemented with the use of electronic networks. It can be produced and distributed electronically, and paid for electronically". 
  • Since its inception, the Internet has continued to change the game for IT and allows business to meet today's "qualitative and quantitative diversification of demand". 
  • Once hidden behind corporate walls and offering immense competitive advantages that could be leveraged into profitability, technology is now openly accessible on the Internet. 
  • Competitors--even small start-ups--can adopt it and level the playing field. As a result, technology itself no longer offers a competitive advantage and higher profit. Instead, the way it is applied to or combined with new information or technologies (i.e., the network effect) creates advantage and profitability. 

Internet

  • Not surprisingly, the same evolution has occurred with digital products, as they are the result of the application of technology. 
  • The Internet now makes the production and distribution of digital products available to a wide audience, whether regulated or not. "We have all become potential publishers". The material we publish may be our original work, a copy of someone else's work, or a combination of the two with virtually no formal quality control.

Insights to develop digital products:

  1. Digital products from a Resource Perspective 
  2. Value Creation in Production and Distribution 
  3. Integrating User-generated Content (UGC) 
  4. Quality Assessment and User Perceptions 
  5. Regulation and Monetization

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