Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Hear also from Adidas, GlobalFoundries, and University of California, Irvine.

AWS 139

AWS Data Warehouse ETL SQL 139

Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. JuMa automatically provisions a new AWS account for the workspace.

ML 140

ML ML AWS AI 140

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

AWS Machine Learning Blog

OCTOBER 28, 2024

This solution offers the following benefits: Seamless integration – SageMaker Canvas empowers you to integrate and use data from various sources, including cloud data warehouses like BigQuery, directly within its no-code ML environment.

Machine Learning 115

Machine Learning Machine Learning ML ML 115

Smart Data Collective

OCTOBER 17, 2022

Engineering teams, in particular, can quickly get overwhelmed by the abundance of information pertaining to competition data, new product and service releases, market developments, and industry trends, resulting in information anxiety. Explosive data growth can be too much to handle. Can’t get to the data.

Big Data 119

Big Data Big Data Data Engineering Data Engineering 119

phData

NOVEMBER 8, 2024

Data Versioning and Time Travel Open Table Formats empower users with time travel capabilities, allowing them to access previous dataset versions. Each snapshot has a separate manifest file that keeps track of the data files associated with that snapshot and hence can be restored/queries whenever needed.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

ODSC - Open Data Science

JANUARY 26, 2024

However, we are making a few changes, most importantly, ODSC East will feature 2 co-located summits, The Data Engineering Summit , and the Ai X Generative AI Summit. In-person attendees will have access to the Ai X Generative Summit and the Data Engineering Summit.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. Data engineers want to catalog data pipelines.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

DataRobot Blog

MARCH 16, 2023

Data scientists run experiments. To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. 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

APRIL 4, 2023

Integrating helpful metadata into user workflows gives all people, from data scientists to analysts , the context they need to use data more effectively. The Benefits and Challenges of the Modern Data Stack Why are such integrations needed? Before a data user leverages any data set, they need to be able to learn about it.

DataOps 52

DataOps Data Engineering Data Engineering Data Engineering 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

phData

MARCH 27, 2024

The SnowPro Advanced Administrator Certification targets Snowflake Administrators, Snowflake Data Cloud Administrators, Database Administrators, Cloud Infrastructure Administrators, and Cloud Data Administrators. I found the Data Engineering Simplified’s playlists particularly beneficial during my studies.

Data Analyst 52

Data Analyst Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

JUNE 16, 2023

Data security posture management is particularly beneficial for organizations that have committed to a cloud-first vision and are moving away from a mixed cloud/on-premises infrastructure. Automatically find and categorize data across all clouds. Avoid exposing cloud data and reduce the attack surface.

Cloud Data 52

Cloud Data Data Science Database Data Scientist 52

Alation

JUNE 7, 2022

Fifth Third faced a number of pain points borne of a large data landscape. The Problem: The Data Challenges. The data challenges at Fifth Third will sound familiar to anyone working in an enterprise data landscape. To meet that growing demand, they decided to make everyone a data citizen.

Data Governance 52

Data Governance Data Scientist Data Engineering Data Engineering 52

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Making this data visible in the data catalog will let data teams share their work, support re-use, and empower everyone to better understand and trust data.

Data Analyst 52

Data Analyst Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

DECEMBER 1, 2023

From data collection and cleaning to feature engineering, model building, tuning, and deployment, ML projects often take months for developers to complete. And experienced data scientists can be hard to come by. The following diagram shows the SageMaker Canvas data flow after adding visual transformations.

Machine Learning 125

Machine Learning Machine Learning Data Preparation ML 125

Alation

AUGUST 16, 2022

This week, IDC released its second IDC MarketScape for Data Catalogs report, and we’re excited to share that Alation was recognized as a leader for the second consecutive time. These include data analysts, stewards, business users , and data engineers. Alation launched Alation Cloud Service (ACS) in April, 2021.

Data Quality 52

Data Quality Data Governance Cloud Data Data Engineering 52

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 Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

JULY 18, 2024

However, creating a computer vision AI requires data scientists to train models for months before they can give results, right? Many data engineering consulting companies could also answer these questions for you, or maybe you think you have the talent on your team to do it in-house. Why phData?

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Data Engineering 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

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And one of the biggest challenges that we see is taking an idea, an experiment, or an ML experiment that data scientists might be running in their notebooks and putting that into production.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And one of the biggest challenges that we see is taking an idea, an experiment, or an ML experiment that data scientists might be running in their notebooks and putting that into production.

SQL 52

SQL ML ML Python 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Jason: I’m curious to learn about your modern data stack.

Data Analyst 52

Data Analyst Data Scientist Analytics Analytics 52

Alation

MARCH 29, 2021

With more data than ever before, the ability to find the right data has become harder than ever. Yet businesses need to find data to make data-driven decisions. However, data engineers, data scientists, data stewards, and chief data officers face the challenge of finding data easily.

Machine Learning 59

Machine Learning Machine Learning Data Lakes Hadoop 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. This allows data scientists to keep their focus on the creation of models or their continuous improvement.

ETL 59

ETL Data Pipeline ML ML 59

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

Alation

DECEMBER 13, 2022

People come to the data catalog to find trusted data, understand it, and use it wisely. Today a modern catalog hosts a wide range of users (like business leaders, data scientists and engineers) and supports an even wider set of use cases (like data governance , self-service , and cloud migration ).

DataOps 52

DataOps Data Governance Data Silos Data Scientist 52

Mlearning.ai

FEBRUARY 16, 2023

Furthermore, a shared-data approach stems from this efficient combination. The background for the Snowflake architecture is metadata management, so customers can enjoy an additional opportunity to share cloud data among users or accounts. Simplify and Win Experienced data engineers value simplicity.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

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

JULY 18, 2023

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. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

phData

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. Building a composable CDP requires some serious data engineering chops.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52