ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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How to Learn Machine Learning

MAY 2, 2025

Welcome to this comprehensive guide on Azure Machine Learning , Microsoft’s powerful cloud-based platform that’s revolutionizing how organizations build, deploy, and manage machine learning models. Sit back, relax, and enjoy this exploration of Azure Machine Learning’s capabilities, benefits, and practical applications.

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Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. When uploading your data, you specify the Machine Learning type, test, and training data before training. Let us get started!

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Dataversity

JULY 9, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with NoSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […]. The post Will They Blend?

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Mlearning.ai

JULY 8, 2023

One of them is Azure functions. In this article we’re going to check what is an Azure function and how we can employ it to create a basic extract, transform and load (ETL) pipeline with minimal code. A batch ETL works under a predefined schedule in which the data are processed at specific points in time.

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ETL Azure Python Internet of Things 52

Towards AI

MARCH 28, 2024

Tune in on YouTube or read the complete article here! In this article, the author aims to share his experience as a software engineer using a question-driven approach to designing an LLM-powered application. Our must-read articles 1. Building an Enterprise Data Lake with Snowflake Data Cloud & Azure using the SDLS Framework.

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ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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Dataversity

MAY 28, 2024

Most enterprises today store and process vast amounts of data from various sources within a centralized repository known as a data warehouse or data lake, where they can analyze it with advanced analytics tools to generate critical business insights.

Analytics 52

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IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. This article endeavors to alleviate those confusions.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed. This pushes into big data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.

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ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. 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.

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Pickl AI

APRIL 21, 2025

Introduction In today’s hyper-connected world, you hear the terms “Big Data” and “Data Science” thrown around constantly. They pop up in news articles, job descriptions, and tech discussions. What exactly is Big Data? It can be confusing!

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The MLOps Blog

JANUARY 23, 2023

As data is the foundation of any machine learning project, it is essential to have a system in place for tracking and managing changes to data over time. However, data versioning control is frequently given little attention, leading to issues such as data inconsistencies and the inability to reproduce results.

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phData

FEBRUARY 14, 2023

If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft. Fivetran works with all three Snowflake cloud providers.

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ODSC - Open Data Science

AUGUST 24, 2023

Bayesian Customer Lifetime Values Modeling using PyMC3 This article is all about implementing BG-NBD, a probabilistic hierarchical model, using PyMC3 to analyze customer purchase behavior. That’s why enriching your analysis with trusted, fit-for-use, third-party data is key to ensuring long-term success.

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Data Lakes Data Science Machine Learning Machine Learning 52

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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ODSC - Open Data Science

JULY 22, 2023

On Wednesday, Henk Boelman, Senior Cloud Advocate at Microsoft, spoke about the current landscape of Microsoft Azure, as well as some interesting use cases and recent developments. Expo Hall ODSC events are more than just data science training and networking events. You can read the recap here and watch the full keynote here.

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Pickl AI

NOVEMBER 4, 2024

The global Big Data and Data Engineering Services market, valued at USD 51,761.6 This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. million by 2028.

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ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. First, articles.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

JULY 11, 2023

6] Questions for AI About Data Centers To learn more about data centers I began by asking ChatGPT what Chief Transformation Officers should know about them. This interaction is described in my upcoming article in CXOTech Magazine. Next, I asked what a data center typically looks like and how it should be staffed.

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The MLOps Blog

JUNE 27, 2023

To provide you with a comprehensive overview, this article explores the key players in the MLOps and FMOps (or LLMOps) ecosystems, encompassing both open-source and closed-source tools, with a focus on highlighting their key features and contributions. Check out the documentation to get started.

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ODSC - Open Data Science

APRIL 3, 2023

Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.

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ODSC - Open Data Science

OCTOBER 20, 2023

At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others.

AI 52

AI AI Data Science Machine Learning 52

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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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.

AI 52

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phData

MARCH 22, 2024

They are Ideal for situations where the data is already stored in data lakes and do not intend to load into Snowflake but need to use the features and performance of Snowflake. To learn more about Iceberg tables in Snowflake, read our article: What are Iceberg Tables in Snowflake and when to use them?

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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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Dataversity

MARCH 29, 2021

The post The Move to Public Cloud and an Intelligent Data Strategy appeared first on DATAVERSITY. Click to learn more about author Joe Gaska. It has taken a global pandemic for organizations to finally realize that the old way of doing businesses – and the legacy technologies and processes that came with it – are no longer going to cut it.

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The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. Cloud ETL Pipeline: Cloud ETL pipeline for ML involves using cloud-based services to extract, transform, and load data into an ML system for training and deployment. Happy Learning!

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The MLOps Blog

MARCH 21, 2023

Learn from the practical experience of four ML teams on collaboration in this article. Data scientists and machine learning engineers need an infrastructure layer that lets them scale their work without having to be networking experts. (in This article defines architecture as the way the highest-level components are wired together.

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Alation

AUGUST 2, 2022

Customer centricity requires modernized data and IT infrastructures. Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics.

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The MLOps Blog

OCTOBER 20, 2023

Nevertheless, many data scientists will agree that they can be really valuable – if used well. And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. There are some outspoken critics , as well as passionate fans. Aside neptune.ai

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