ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. million by 2028.

Data Engineering 52

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Precisely

MARCH 27, 2023

Staffed by experienced enterprise professionals with an average of nearly 25 tenure years, Precisely Strategic Services is proud to have earned a reputation as a top-tier data-centric management consulting organization. This article offers a few examples that illustrate some of the most popular use cases for data-driven strategic services.

Data Quality 52

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O'Reilly Media

OCTOBER 19, 2021

In this article, we want to dig deeper into the fundamentals of machine learning as an engineering discipline and outline answers to key questions: Why does ML need special treatment in the first place? ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

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Alation

JULY 19, 2022

The traditional data science workflow , as defined by Joe Blitzstein and Hanspeter Pfister of Harvard University, contains 5 key steps: Ask a question. Get the data. Explore the data. Model the data. A data catalog can assist directly with every step, but model development.

Data Scientist 59

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AWS Machine Learning Blog

MAY 31, 2024

AWS offers a GDPR-compliant AWS Data Processing Addendum (AWS DPA), which helps you to comply with GDPR contractual obligations. The AWS DPA is incorporated into the AWS Service Terms. Krishna Prasad is a Senior Solutions Architect in Strategic Accounts Solutions Architecture team at AWS.

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DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Many find themselves swamped by the volume and complexity of unstructured data.

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DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

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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. Model versioning, lineage, and packaging : Can you version and reproduce models and experiments? Can you render audio/video?

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phData

MAY 13, 2024

This article was co-written by Justin Delisi & Sam Hall. Simple Data and Infrastructure Management Snowflake separates compute from storage, automatically scaling up or down instantly and independently based on your needs. Additionally, change data markers are not available for many of these tables.

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Dataversity

MARCH 22, 2021

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.

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Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

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ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. ArangoDB ArangoDB is a company that provides a database platform for graph and document data.

Machine Learning 52

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Mlearning.ai

FEBRUARY 16, 2023

In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently. The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. What makes Snowflake so unique, and are there any caveats to it?

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The Data Administration Newsletter

JULY 17, 2024

They are interesting to an extent, but mostly, they feel like a late-night re-run and remind me that data work is hard. If you haven’t heard about metrics stores yet, they’re “newish,” so you likely will. So, what is a metrics store? Most of the young vendors trying to create this category will tell you that […]

Data Lakes 52

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Dataversity

AUGUST 21, 2023

A collection of facts from which inferences can be made is called data. Data is the cornerstone of contemporary society and is crucial to many facets of people’s lives. In order to gain knowledge and make wise decisions, […] The post Data Provisioning: Ingest, Curate, and Publish appeared first on DATAVERSITY.

Data Lakes 52

Data Lakes Data Warehouse Data Modeling Data Models 52

The MLOps Blog

MARCH 15, 2023

If you will ask data professionals about what is the most challenging part of their day to day work, you will likely discover their concerns around managing different aspects of data before they get to graduate to the data modeling stage.

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The MLOps Blog

MAY 9, 2023

It lets them focus more on deploying new models than maintaining existing ones. It provides the ability to focus on new models instead of putting too much effort into maintaining existing models. In this article, you will: 1 Explore what the architecture of an ML pipeline looks like, including the components.

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