Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Metadata layer 4. This starts at the data source.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Metadata layer 4. This starts at the data source.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 16, 2024

And with so many data teams across functions, how does Fox approach data governance? Table of Contents Solve data silos starting at the people-level Keep data governance approachable Oliver Gomes’ data governance best practices Manage and promote the value of high-quality data How will Generative AI impact data quality at Fox?

Government 52

Government High Quality Data Data Governance Entertainment 52

Monte Carlo

JANUARY 23, 2024

Given that Max and his team couldn’t take a customer’s entire database, or even just the metadata, and fit it in the context window, “We realized we needed to be really smart about RAG, which is retrieving the right information to generate the right SQL. It can show me how it built that chart, which dataset it used, and show me the metadata.”

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

DataKitchen

SEPTEMBER 21, 2023

This proactive approach to data quality guarantees that downstream analytics and business decisions are based on reliable, high-quality data, thereby mitigating the risks associated with poor data quality. There are multiple locations where problems can happen in a data and analytic system.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Maxime Beauchemin

JANUARY 20, 2017

I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence. I wasn’t promoted or assigned to this new role.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Ascend.io

JUNE 8, 2023

Is it possible to treat data not just as a necessary operational output, but as a product that holds immense strategic value? Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52