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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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SMAC - $1 Trillion Industry By 2020

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At least 5-6 lakh people will soon be employed in the space, according to Ganesh Natarajan, CEO, Zensar Technologies

The size of the overall SMAC industry globally will be close to $1 trillion by 2020. From the Indian software exporters’ point of view, it will be $15 billion within the next three years, and over $ 225 Billion by 2020.
Translating that to people it would mean at least 5-6 lakh people employed in this space by that time.
Zensar Technologies has a Digital Enterprise group focusing on digital transformation solutions, where we work with clients in the US, Europe and India to understand what applications can be taken to the Cloud, which is almost 30 per cent of the SMAC opportunity.
The second area is Social Listening involving analysis of information on the social media. Zensar provides a service that will enable our clients, especially those who are interacting with consumers directly and often, like insurance companies, retail banks, etc. on how to improve their marketing initiatives or service quality etc. This service involves a rich interweave of social media monitoring and applying analytics to it to help the client make informed decisions and very often in real time. A lot of marketing analytics is based on what is happening in the social media today. Increasing number of users are the Gen Y, and being digital natives their access to social media and their use of it for any transaction is immense, thus churning out a lot of data all the time. Big Data is about combining intelligence from your own measuring systems with what the world is talking about you.

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