ODSC - Open Data Science

FEBRUARY 14, 2023

We’ve just wrapped up our first-ever Data Engineering Summit. If you weren’t able to make it, don’t worry, you can watch the sessions on-demand and keep up-to-date on essential data engineering tools and skills. Joe Reis addresses the current economic climate in 2023 in particular.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

APRIL 6, 2023

Automate and streamline our ML inference pipeline with SageMaker and Airflow Building an inference data pipeline on large datasets is a challenge many companies face. Airflow setup Apache Airflow is an open-source tool for orchestrating workflows and data processing pipelines. ", instance_type="ml.m5.xlarge",

Data Pipeline 52

Data Pipeline ML ML AWS 52

The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

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Machine Learning Machine Learning ML ML 134

ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. However, each year the skills and certainly the platforms change somewhat.

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Data Science Data Scientist Computer Science Computer Science 98

Towards AI

OCTOBER 31, 2024

In marketing, for example, AI helps organizations extract actionable insights from vast data sets, leading to targeted campaigns and better customer engagement. Hype Cycle for Emerging Technologies 2023 (source: Gartner) Despite AI’s potential, the quality of input data remains crucial.

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Data Quality Analytics Analytics Clean Data 100

Alation

MAY 31, 2023

This year’s DGIQ West will host tutorials, workshops, seminars, general conference sessions, and case studies for global data leaders. DGIQ is June 5-9, 2023, at the Catamaran Resort Hotel and Spa in San Diego, just steps away from the Mission Bay beach. You can learn more about the event and register here.

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Data Governance DataOps Data Pipeline Business Intelligence 52

DagsHub

SEPTEMBER 10, 2023

Low to non-code Open Source Machine Learning Datasets : Enrich the open-source dataset domain and enhance its accessibility and capabilities by exposing them to DagsHub Data Engine, unlocking unique data management capabilities. What Machine Learning projects participate in Hacktoberfest?

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

ODSC - Open Data Science

DECEMBER 14, 2023

Data Engineering vs Machine Learning Pipelines This tutorial explores the differences between how machine learning and data pipelines work, as well as what is required for each.

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K-nearest Neighbors AI AI Machine Learning 97

Towards AI

OCTOBER 4, 2023

Last Updated on October 6, 2023 by Editorial Team Author(s): ????Mike Advanced-Data Engineering and ML Ops with Infrastructure as Code This member-only story is on us. Mike Shakhomirov Originally published on Towards AI. Upgrade to access all of Medium.

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Machine Learning Machine Learning AWS ML 59

IBM Data Science in Practice

MARCH 8, 2023

Hidden Technical Debt in Machine Learning Systems More money, more problems — Rise of too many ML tools 2012 vs 2023 — Source: Matt Turck People often believe that money is the solution to a problem. A feature platform should automatically process the data pipelines to calculate that feature. Spark, Flink, etc.)

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Machine Learning Machine Learning ML ML 264

phData

JUNE 26, 2024

Cleaning and preparing the data Raw data typically shouldn’t be used in machine learning models as it’ll throw off the prediction. Data engineers can prepare the data by removing duplicates, dealing with outliers, standardizing data types and precision between data sets, and joining data sets together.

Machine Learning 52

Machine Learning Machine Learning Data Engineer Data Engineering 52

phData

NOVEMBER 2, 2023

Managing data pipelines efficiently is paramount for any organization. The Snowflake Data Cloud has introduced a groundbreaking feature that promises to simplify and supercharge this process: Snowflake Dynamic Tables. Flexibility: Dynamic tables allow batch and streaming pipelines to be specified in the same way.

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Data Pipeline SQL Data Warehouse Data Engineer 52

phData

NOVEMBER 28, 2023

In July 2023, Matillion launched their fully SaaS platform called Data Productivity Cloud, aiming to create a future-ready, everyone-ready, and AI-ready environment that companies can easily adopt and start automating their data pipelines coding, low-coding, or even no-coding at all.

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Data Warehouse Data Pipeline ETL Azure 52

phData

FEBRUARY 8, 2024

Data Modeling, dbt has gradually emerged as a powerful tool that largely simplifies the process of building and handling data pipelines. dbt is an open-source command-line tool that allows data engineers to transform, test, and document the data into one single hub which follows the best practices of software engineering.

Data Modeling 52

Data Modeling Data Models Data Warehouse Database 52

phData

JULY 18, 2024

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. 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.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Data Engineer 52

ODSC - Open Data Science

APRIL 26, 2023

Tools such as the mentioned are critical for anyone interested in becoming a machine learning engineer. Data Engineer Data engineers are the authors of the infrastructure that stores, processes, and manages the large volumes of data an organization has. Well then, you’re in luck.

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Data Analyst Machine Learning Machine Learning Power BI 52

phData

MARCH 22, 2023

Top Use Cases of Snowpark With Snowpark, bringing business logic to data in the cloud couldn’t be easier. Transitioning work to Snowpark allows for faster ML deployment, easier scaling, and robust data pipeline development. ML Applications For data scientists, models can be developed in Python with common machine learning tools.

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ML ML Machine Learning Machine Learning 52

AWS Machine Learning Blog

JUNE 18, 2024

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. Having a human-in-the-loop to validate each data transformation step is optional.

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The MLOps Blog

JANUARY 23, 2023

However, there are some key differences that we need to consider: Size and complexity of the data In machine learning, we are often working with much larger data. Basically, every machine learning project needs data. Given the range of tools and data types, a separate data versioning logic will be necessary.

ML 52

ML ML Data Lakes Machine Learning 52

Snorkel AI

JUNE 22, 2023

So, in those projects, you have more than 70% of the engineering development resources that are tied to data engineering activities. That is a mix of data engineering, feature engineering work, a mix of data transformation work writ large. It is at the level of data quality and joining tasks.

Data Quality 52

Data Quality AI AI ML 52

Snorkel AI

JUNE 22, 2023

So, in those projects, you have more than 70% of the engineering development resources that are tied to data engineering activities. That is a mix of data engineering, feature engineering work, a mix of data transformation work writ large. It is at the level of data quality and joining tasks.

Data Quality 52

Data Quality AI AI ML 52

phData

JULY 5, 2024

In a survey conducted in 2023 , over three-quarters of the executives surveyed believed that artificial intelligence would disrupt their business strategy. To provide an example, traditional structured data such as a user’s demographic information can be provided to an AI application to create a more personable experience.

AI 52

AI AI Database AWS 52

phData

DECEMBER 4, 2023

Data Pipelines “Data pipeline” means moving data in a consistent, secure, and reliable way at some frequency that meets your requirements. Data pipelines can be built with third-party tools alone or in conjunction with Snowflake’s tools. Use with caution, and test before committing to using them.

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Clustering Database SQL Data Pipeline 98

DataRobot Blog

APRIL 1, 2018

In Nick Heudecker’s session on Driving Analytics Success with Data Engineering , we learned about the rise of the data engineer role – a jack-of-all-trades data maverick who resides either in the line of business or IT. 3) The emergence of a new enterprise information management platform.

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Analytics Analytics Data Preparation Augmented Analytics 40

Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. Continuous monitoring of resources, data, and metrics. Data Pipeline - Manages and processes various data sources. LLMOps is MLOps for LLMs.

ML 52

ML ML AI AI 52

phData

SEPTEMBER 27, 2024

In transitional modeling, we’d add new atoms: Subject: Customer#1234 Predicate: hasEmailAddress Object: "john.new@example.com" Timestamp: 2023-07-24T10:00:00Z The old email address atoms are still there, giving us a complete history of how to contact John. Both persistent staging and data lakes involve storing large amounts of raw data.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

AWS Machine Learning Blog

MARCH 15, 2024

In Dr. Werner Vogels’s own words at AWS re:Invent 2023 , “every second that a person has a stroke counts.” Medical data restrictions You can use machine learning (ML) to assist doctors and researchers in diagnosis tasks, thereby speeding up the process. He has worked with multiple federal agencies to advance their data and AI goals.

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phData

JULY 12, 2023

In this blog, we’ll explore how Matillion Jobs can simplify the data transformation process by allowing users to visualize the data flow of a job from start to finish. With that, let’s dive in! What is Matillion ETL? Suppose we have the following insert statement: INSERT INTO orders_by_city SELECT o.id

SQL 52

SQL ETL Database Data Pipeline 52

phData

APRIL 21, 2023

In this blog, we’ll explore how Matillion Jobs can simplify the data transformation process by allowing users to visualize the data flow of a job from start to finish. With that, let’s dive in What is Matillion ETL? Suppose we have the following insert statement: INSERT INTO orders_by_city SELECT o.id

SQL 52

SQL ETL Database Data Pipeline 52

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Simplify and Win Experienced data engineers value simplicity. Originally published at [link] on February 9, 2023.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 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.

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AI AI Machine Learning Machine Learning 75

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. Let’s go and talk about machine learning pipelining.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. Let’s go and talk about machine learning pipelining.

SQL 52

SQL ML ML Python 52

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Monthly Updates Microsoft shows continual investment in the product and its user base by updating Power BI monthly.

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Power BI Analytics Analytics Azure 84

Snorkel AI

MAY 12, 2023

The reason is that most teams do not have access to a robust data ecosystem for ML development. billion is lost by Fortune 500 companies because of broken data pipelines and communications. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

The reason is that most teams do not have access to a robust data ecosystem for ML development. billion is lost by Fortune 500 companies because of broken data pipelines and communications. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Context In early 2023, Zeta’s machine learning (ML) teams shifted from traditional vertical teams to a more dynamic horizontal structure, introducing the concept of pods comprising diverse skill sets. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

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