Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. Many organizations are using CDC technology to push data to cloud data platforms like Snowflake, Redshift, Databricks, and Kafka.

Data Silos 52

Data Silos ETL Data Quality Data Pipeline 52

IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. Watsonx.data allows customers to augment data warehouses such as Db2 Warehouse and Netezza and optimize workloads for performance and cost. IBM watsonx.ai

AI 74

AI AI Machine Learning Machine Learning 74

phData

SEPTEMBER 4, 2024

ThoughtSpot was designed to be low-code and easy for anyone to use across a business to generate insights and explore data. ThoughSpot can easily connect to top cloud data platforms such as Snowflake AI Data Cloud , Oracle, SAP HANA, and Google BigQuery.

Analytics 52

Analytics Analytics SQL ETL 52

phData

JULY 18, 2023

Why Migrate to a Modern Data Stack? With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. Legacy tools force users to manually build out processes that can be automated by the Modern Data Stack.

Data Warehouse 52

Data Warehouse Analytics Analytics SQL 52

Alation

APRIL 4, 2023

The people navigating these increasingly chaotic landscapes need a single place to find, understand, and use data with total confidence. Expanded Integration with Databricks Unity Catalog Unity Catalog is Databricks ’ governance and admin layer for all lakehouse data and AI assets, including files, tables, ML models, and dashboards.

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52

Alation

JANUARY 25, 2022

This “analysis” is made possible in large part through machine learning (ML); the patterns and connections ML detects are then served to the data catalog (and other tools), which these tools leverage to make people- and machine-facing recommendations about data management and data integrations.

DataOps 52

DataOps SQL ML ML 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. You can use stored procedures to handle complex ETL processes, make API calls, and perform data validation.

SQL 52

SQL Database Apache Hadoop Data Science 52

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In “The modern data stack is dead, long live the modern data stack!” Cloud costs are growing prohibitive.

Data Pipeline 52

Data Pipeline Data Warehouse Cloud Data ETL 52

phData

SEPTEMBER 27, 2024

If the event log is your customer’s diary, think of persistent staging as their scrapbook – a place where raw customer data is collected, organized, and kept for future reference. In traditional ETL (Extract, Transform, Load) processes in CDPs, staging areas were often temporary holding pens for data.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52