Tame Your Databricks Spend: Expert Optimization for Cost-Effective Data & AI
Let's explore how XTIVIA can help you optimize your Databricks spend and environment and achieve maximum ROI.| XTIVIA
For many enterprises, databases are more than just storage—they’re the backbone of institutional memory. Over years, sometimes decades, companies accumulate valuable business logic, performance patterns, and decision-making frameworks embedded deep within legacy systems. But as technology rapidly evolves, clinging to outdated infrastructure becomes a liability. The challenge? Modernizing without compromising... Read more » The post Database modernization without losing decades of accumul...| Big Data Analytics News
Let's explore how XTIVIA can help you optimize your Databricks spend and environment and achieve maximum ROI.| XTIVIA
You know, after literally multiple decades in the data space, writing code and SQL, at some point along that arduous journey, one might think this problem would be solved by me, or the tooling … yet alas, not to be. Regardless of the industry or tools used, such as Pandas, Spark, or Postgres, duplicates are […] The post Duplicates in Data and SQL appeared first on Confessions of a Data Guy.| Confessions of a Data Guy
Each time I compile and curate the Database Weekly newsletter, I find lots of Fabric content from the various sources I watch to compose the newsletter. Since I primarily deal with the Microsoft Da…| Voice of the DBA
The SAP and Databricks partnership and the introduction of SAP Business Data Cloud. Jan van Ansem from Snap Analytics explains what it means for customers. The post The SAP Databricks partnership: Combining expert knowledge of business critical processes with world-class data engineering capabilities appeared first on Snap Analytics.| Snap Analytics
The first five posts of these series were largely conceptual discussions that sprinkled in some SQL and data models here and there where helpful. This final post will serve as a summary of those posts, but it will also specifically include SQL queries, data models and transformation logic related to the overall discussion that should […] The post Tied With A Bow: Wrapping Up the Hierarchy Discussion (Part 6 of 6) appeared first on Snap Analytics.| Snap Analytics
In the first three posts of this series, we delved into some necessary details from graph theory, reviewed acyclic graphs (DAGs), and touched on some foundational concepts that help describe what hierarchies are and how they might best be modeled. In the fourth post of the series, we spent time considering an alternative model for […] The post Edge Cases: Handling Ragged and Unbalanced Hierarchies (Part 5 of 6) appeared first on Snap Analytics.| Snap Analytics
In the first post of this series, we walked through the basic concepts of a graph. In the second post, we discussed a particular kind of graph called a directed acyclic graph (DAG) and helped disambiguate and extend the roles it plays in data engineering. In the third post, we further constrained the definition of […] The post Flat Out: Introducing Level Hierarchies (4 of 6) appeared first on Snap Analytics.| Snap Analytics
Sometimes, the only thing standing between an analyst and a catastrophic management decision could be knowing the difference between the tables:| Blog
Data warehouses are becoming increasingly popular as many businesses, nonprofits, and municipal organizations realize the value of storing their current and historic data in a dynamic and useful way.| Blog
Running dbt on Databricks has never been easier. The integration between dbtcore and Databricks could not be more simple to set up and run. Wondering how to approach running dbt models on Databricks with SparkSQL? Watch the tutorial below.| Confessions of a Data Guy
There are things in life that are satisfying—like a clean DAG run, a freshly brewed cup of coffee, or finally deleting 400 lines of YAML. Then there are things that make you question your life choices. Enter: setting up Apache Polaris (incubating) as an Apache Iceberg REST catalog. Let’s get one thing out of the […]| Confessions of a Data Guy
In this blog, find out about the different types of data marts, examples, their uses, and how you can implement them for your business.| Astera
Data-driven decisions based on accurate and reliable insights help you derive substantial business value. Find out more!| Astera
ELT is the modern data integration approach that transforms that after it is loaded into the destination. Here's all you need to know!| Astera
Matillion Shared Jobs help making ETL solutions consistent, easy to support and cheaper to manage. Here are the key benefits explained.| Snap Analytics
This blog post explains the basic concepts of data warehousing and further elaborates on the uses of data warehouses in different industries.| Astera
IBM has taken another open source technology provider into its portfolio, acquiring Ahana, one of the leading vendors behind the massively parallel distributed in-memory SQL query engine Presto. Presto, first created and still actively developed at Meta, has attracted a broad array of open source contributors, and is championed by several vendors. It has alsoContinue reading "IBM and Ahana – A Lakehouse Down Payment"| IT Market Strategy
Tom Breur 13 August 2019 Recently, I was reading a whitepaper from a large vendor: “ … access to democratized data” and it got me wondering. What does “data democracy” stand for? The way the phrase…| Data, Analytics and beyond
