Since leaving university, I have always been involved with data, learning so much during my time as an automation engineer and big data engineer working for an automotive tier 1 manufacturing company and as a data architect for an IT consultancy in the SAP and BI domain. And today, I count myself very fortunate to have a job at Kensu that I am truly passionate about. As a Technical Solution Architect, I get to help organizations with data health and data engineering problems on a daily basis!

Last week’s announcement of a data fabric approach from Microsoft was interesting to us on a number of levels, most notably for what it confirmed: Data Fabrics are now mainstream. If you’ve not heard why Data Fabrics are the next big thing, then here is a bit of history. Data Fabric is a concept that started to take hold over a decade ago with published research from Forrester.

In today's fast-paced and ever-evolving business landscape, organizations are constantly striving to gain a competitive edge, make well-informed decisions, and fuel their growth. As a result, advanced Business Intelligence (BI) tools have emerged, revolutionizing the way businesses harness the power of data to drive their success. These sophisticated BI tools offer a wide range of capabilities, empowering companies to collect, analyze, and visualize data from various sources.

Bulk data exports in the Google Search console let you export search data to BigQuery and run complex queries and create custom reports on it.

BigQuery object tables offer a structured record interface for unstructured data, so you can process and manage it securely and programmatically.

The BigQuery partitioning and clustering recommender analyzes workloads and tables and identifies potential cost-optimization opportunities.

A continuation of our series on ASCII files; how to ingest data from HL7 files.