phData

JANUARY 5, 2023

Python is the top programming language used by data engineers in almost every industry. Python has proven proficient in setting up pipelines, maintaining data flows, and transforming data with its simple syntax and proficiency in automation. Why Connect Snowflake to Python?

Python 52

Python Data Engineering Data Engineering Data Engineering 52

Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Towards AI

JANUARY 28, 2024

To start, get to know some key terms from the demo: Snowflake: The centralized source of truth for our initial data Magic ETL: Domo’s tool for combining and preparing data tables ERP: A supplemental data source from Salesforce Geographic: A supplemental data source (i.e., Instagram) used in the demo Why Snowflake?

ETL 111

ETL Python Database Data Preparation 111

DataRobot

MAY 11, 2021

Founded in 2016 by the creator of Apache Zeppelin, Zepl provides a self-service data science notebook solution for advanced data scientists to do exploratory, code-centric work in Python, R, and Scala. Data Exploration, Visualization, and First-Class Integration. And Even More to Come in 2021.

Data Scientist 98

Data Scientist Citizen Data Scientist Data Science AI 98

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

phData

AUGUST 6, 2024

Organizations must ensure their data pipelines are well designed and implemented to achieve this, especially as their engagement with cloud data platforms such as the Snowflake Data Cloud grows. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

Data Pipeline 52

Data Pipeline Python Data Engineering Data Engineering 52

Flipboard

NOVEMBER 24, 2023

JuMa is a service of BMW Group’s AI platform for its data analysts, ML engineers, and data scientists that provides a user-friendly workspace with an integrated development environment (IDE). It is powered by Amazon SageMaker Studio and provides JupyterLab for Python and Posit Workbench for R.

ML 149

ML ML AWS Data Scientist 149

phData

FEBRUARY 7, 2024

The Snowflake Data Cloud is a leading cloud data platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is called Snowpark, which provides an intuitive library for querying and processing data at scale in Snowflake.

Python 52

Python ML ML SQL 52

AWS Machine Learning Blog

DECEMBER 1, 2023

Proper data preparation leads to better model performance and more accurate predictions. SageMaker Canvas allows interactive data exploration, transformation, and preparation without writing any SQL or Python code. SageMaker Canvas recently added a Chat with data option. On the Create menu, choose Document.

Machine Learning 121

Machine Learning Machine Learning Data Preparation ML 121

phData

SEPTEMBER 2, 2024

Best practices are a pivotal part of any software development, and data engineering is no exception. This ensures the data pipelines we create are robust, durable, and secure, providing the desired data to the organization effectively and consistently. Below are the best practices. Schedules cannot be edited or executed.

ETL 52

ETL Data Warehouse SQL Database 52

AWS Machine Learning Blog

OCTOBER 18, 2023

Deployment with the AWS CDK The Step Functions state machine and associated infrastructure (including Lambda functions, CodeBuild projects, and Systems Manager parameters) are deployed with the AWS CDK using Python. He is passionate about helping customers to build scalable and modern data analytics solutions to gain insights from the data.

AWS 128

AWS ML ML Machine Learning 128

DataRobot Blog

MARCH 16, 2023

The DataRobot team has been working hard on new integrations that make data scientists more agile and meet the needs of enterprise IT, starting with Snowflake. We’ve tightened the loop between ML data prep , experimentation and testing all the way through to putting models into production.

Data Scientist 52

Data Scientist ML ML Data Preparation 52

Alation

MARCH 1, 2022

Through Impact Analysis, users can determine if a problem occurred with data upstream, and locate the impacted data downstream. With robust data lineage, data engineers can find and fix issues fast and prevent them from recurring. Similarly, analysts gain a clear view of how data is created.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

phData

MARCH 29, 2023

However, many analysts and other data professionals run into two common problems: They are not given direct access to their database They lack the skills in SQL to write the queries themselves The traditional solution to these problems is to rely on IT and data engineering teams. What can be done?

Database 52

Database SQL Analytics Analytics 52

IBM Journey to AI blog

JULY 17, 2023

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities. Savings may vary depending on configurations, workloads and vendor.

AI 74

AI AI Machine Learning Machine Learning 74

Alation

JANUARY 17, 2023

These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? The rise of cloud computing and cloud data warehousing has catalyzed the growth of the modern data stack. Data scientists.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

FEBRUARY 14, 2023

Matillion Matillion is a complete ETL tool that integrates with an extensive list of pre-built data source connectors, loads data into cloud data environments such as Snowflake, and then performs transformations to make data consumable by analytics tools such as Tableau and PowerBI.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

The MLOps Blog

MAY 17, 2023

This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines. Create a python function file that consists of all the ETL tasks – etl_functions.py.

ETL 59

ETL Data Pipeline ML ML 59

phData

SEPTEMBER 4, 2024

ThoughtSpot is a cloud-based AI-powered analytics platform that uses natural language processing (NLP) or natural language query (NLQ) to quickly query results and generate visualizations without the user needing to know any SQL or table relations. Suppose your business requires more robust capabilities across your technology stack.

Analytics 52

Analytics Analytics SQL ETL 52

phData

DECEMBER 4, 2023

However, if there’s one thing we’ve learned from years of successful cloud data implementations here at phData, it’s the importance of: Defining and implementing processes Building automation, and Performing configuration …even before you create the first user account. You can use whatever works best for your technology.

Clustering 98

Clustering Database SQL Data Pipeline 98

Data Science Blog

SEPTEMBER 3, 2024

Celonis versucht Machine Learning innerhalb der Plattform aus einer Hand anzubieten und hat auch eigene Python-Bibleotheken dafür entwickelt. Reduzierte Personalkosten , sind oft dann gegeben, wenn interne Data Engineers verfügbar sind, die die Datenmodelle intern entwickeln. Bisher dreht sich hier viel eher noch um z.

Data Science 130

Data Science Power BI Azure Data Warehouse 130