phData

NOVEMBER 4, 2024

Snowflake excels in efficient data storage and governance, while Dataiku provides the tooling to operationalize advanced analytics and machine learning models. Together they create a powerful, flexible, and scalable foundation for modern data applications.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

IBM Journey to AI blog

SEPTEMBER 19, 2023

By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

MAY 15, 2024

Dreaming of a Data Science career but started as an Analyst? This guide unlocks the path from Data Analyst to Data Scientist Architect. The Insights This comprehensive guide, updated for 2024, delves into the challenges and strategies associated with scaling Data Science careers.

Data Analyst 52

Data Analyst Data Scientist Data Science Machine Learning 52

ODSC - Open Data Science

JANUARY 18, 2024

If you are a data scientist, you may be wondering if you can transition into data engineering. The good news is that there are many skills that data scientists already have that are transferable to data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

MARCH 20, 2024

Jinja’s usage will significantly empower you to build dynamic and reusable data pipelines , especially when dealing with conditional logic and templatization within dbt. In this blog, we will extract the essence of Jinja in dbt. What is Jinja? Jinja is a powerful and versatile templating engine. Round 11.123 | round(1) 11.1

SQL 52

SQL Data Wrangling Database Python 52

phData

FEBRUARY 14, 2023

To keep up with the rapidly growing Insurance industry and its increasing data and compute needs, it’s important to centralize data from multiple sources while maintaining high performance and concurrency. Also today’s volume, variety, and velocity of data, only intensify the data-sharing issues.

Data Governance 52

Data Governance Data Silos Predictive Analytics Data Scientist 52

Pickl AI

JUNE 7, 2024

At the heart of this process lie ETL Tools—Extract, Transform, Load—a trio that extracts data, tweaks it, and loads it into a destination. Choosing the right ETL tool is crucial for smooth data management. This blog will delve into ETL Tools, exploring the top contenders and their roles in modern data integration.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40