datapine

SEPTEMBER 27, 2022

17) “SQL Database Programming” (2015 Edition) By Chris Fehily. The all-encompassing nature of this book makes it a must for a data bookshelf. 18) “The Data Warehouse Toolkit” By Ralph Kimball and Margy Ross. It is a must-read for understanding data warehouse design. Viescas, Douglas J. Steele, and Ben J.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Alation

DECEMBER 15, 2022

December 2012: Alation forms and goes to work creating the first enterprise data catalog. Later, in its inaugural report on data catalogs, Forrester Research recognizes that “Alation started the MLDC trend.”. January 2015: Alation acquires its first customer. April 2016: Tesco Group becomes first customer outside North America.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. This is where the observant reader will see the concept of Convergent Evolution playing out in the data arena as well as the Natural World. This is the essence of Convergent Evolution. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 55

Analytics Data Lake Testing Optimization 55

Howard Dresner

JANUARY 4, 2015

But I’ll make an exception now – I predict that we’ll see even more success in BI initiatives in 2015 if organizations eliminate these “gotchas” from their practice. As I often tell journalists and inquirers, I don’t have a crystal ball and don’t make predictions.

Business Intelligence 45

Business Intelligence Recreation/Entertainment Sales Data Quality 45

AWS Big Data

FEBRUARY 1, 2023

Clients access this data store with an API’s. Amazon S3 as data lake For better data quality, we extracted the enriched data into another S3 bucket with the same AWS Glue job. Every dataset in our system is uniquely identified by snapshot ID, which we can search from our metadata store.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Domino Data Lab

FEBRUARY 4, 2019

In my experience, hyper-specialization tends to seep into larger organizations in a special way… If a company is say, more than 10 years old, they probably began analytics work with a business intelligence team using a data warehouse. Lack of data, or data quality issues (silos). Friction ensued.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66