Tableau

DECEMBER 1, 2021

Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases. The prototype could connect to multiple data sources at the same time—a precursor to Tableau’s investments in data federation. The Data Tab was added in v8.2

Tableau 145

Tableau ML ML Database 145

phData

MAY 25, 2023

Two of the platforms that we see emerging as a popular combination of data warehousing and business intelligence are the Snowflake Data Cloud and Power BI. Debuting in 2015, Power BI has undergone meaningful updates that have made it a leader not just in data visualization, but in the business intelligence space as well.

Power BI 84

Power BI Analytics Analytics Azure 84

Pickl AI

MAY 16, 2023

For example, if you are a Data Scientist, then you should add keywords like Python, SQL, Machine Learning, Big Data and others. These are some of the key skills that one needs to have if you are eyeing a fulfilling career as a Data Scientist. Highlight Your Experience Don’t miss this part. Wrapping it up !!!

Data Scientist 52

Data Scientist Data Science SQL Python 52

Tableau

DECEMBER 1, 2021

Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases. The prototype could connect to multiple data sources at the same time—a precursor to Tableau’s investments in data federation. The Data Tab was added in v8.2

Tableau 98

Tableau ML ML Database 98

Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. Many of our customers successfully build fast and scalable graph visualization applications without a graph database. With data stored as a graph, it makes sense to query it as a graph too. .”

Database 59

Database Azure Analytics Analytics 59

ODSC - Open Data Science

JANUARY 29, 2024

Data science methodologies and skills can be leveraged to design these experiments, analyze results, and iteratively improve prompt strategies. Using skills such as statistical analysis and data visualization techniques, prompt engineers can assess the effectiveness of different prompts and understand patterns in the responses.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52