Data Technology Trend #8: Data Next — part 4

LAKSHMI VENKATESH
4 min readJun 21, 2021

This article is a part of a multi-part series Data Technology Trends (parent article). Previous article — Link: Data Technology Trend #7: Monetized. Previous part of this trend — Data Technology Trend #8: Data Next — part 3 and next part of this trend — Data Technology Trend #8: Data Next — part 5.

Trend 8.1 Unified and Enriched Big Data and AI — Delta Lake

Few impressive features of Delta Lake: (Cont..)

5. Delta tables to Delta Live Tables

As we saw earlier, the foundation of Lakehouse architecture is having Bronze — row data; Silver — filtered, cleaned augmented data, and Gold — Business level aggregates. This is the simplest form. But in reality, as the producers increase and consumers increase and if we are not adopting any of the modern features such as Unity Catalog, we may end up having multiple Bronze, Silver, and Gold buckets. This makes it difficult to maintain a reliable version of data and the Data Lake will soon end up being Data Swamp. In order to preserve the single version of the truth and the reliability of data, Databricks announces “Delta Live Table”, a reliable ETL made easy with Delta Lake.

What is Delta Live Table:

Delta Live Table, as the name suggests, shares the live data as and when some changes happen to the underlying data set.

Key Features:

1. Delta live tables understand your data pipeline

2. Live table understands your dependencies

3. It does automatic monitoring and recovery

4. Enables automatic environment independent data management

a. Different copies of data can be isolated and updated using the same code base.

5. Treat your data as code

LAKSHMI VENKATESH

All the views expressed here are my own views and does not represent views of my firm that I work for. Data | Big Data | Cloud | ML