TransOrg Analytics

AUGUST 9, 2024

In the realm of data management and analytics, businesses face a myriad of options to store, manage, and utilize their data effectively. Understanding their differences, advantages, and ideal use cases is crucial for making informed decisions about your data strategy. Cons: Costly: Can be expensive to implement and maintain.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52

The MLOps Blog

MAY 31, 2023

You may also like Building a Machine Learning Platform [Definitive Guide] Consideration for data platform Setting up the Data Platform in the right way is key to the success of an ML Platform. In the following sections, we will discuss best practices while setting up a Data Platform for Retail.

ML 59

ML Algorithm Data Drift Machine Learning 59

Pickl AI

DECEMBER 16, 2024

Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals. Key Takeaways Microsoft Fabric is a full-scale data platform, while Power BI focuses on visualising insights. Its strength lies in visualising and analysing data rather than managing it.

ETL 52

ETL Data Ingestion Data Integration Machine Learning 52

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

ODSC - Open Data Science

OCTOBER 9, 2024

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Software Engineer 40

Software Engineer Software Development DevOps Machine Learning 40

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

Arjuna Chala, associate vice president, HPCC Systems For those not familiar with the HPCC Systems data lake platform, can you describe your organization and the development history behind HPCC Systems? They were interested in creating a data platform capable of managing a sizable number of datasets.

Big Data 52

Big Data ETL Data Science Data Ingestion 52

AWS Machine Learning Blog

SEPTEMBER 6, 2024

By following these guidelines, data scientists can quantify the user experience delivered by their generative AI pipelines and communicate meaning to business stakeholders, facilitating ready comparisons across different architectures, such as Retrieval Augmented Generation (RAG) pipelines, off-the-shelf or fine-tuned LLMs, or agentic solutions.

Generative AI 92

Generative AI LLM AI AI 92

Artificial Corner

JUNE 6, 2023

Spark offered a more versatile programming model, supporting not only MapReduce-like batch processing but also real-time stream processing and interactive data queries. Its ability to efficiently handle iterative algorithms and machine learning tasks made it a popular choice for data scientists and engineers. Morgan Kaufmann.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Flipboard

DECEMBER 4, 2024

It often requires multiple teams working together and integrating various data sources, tools, and services. For example, creating a targeted marketing app involves data engineers, data scientists, and business analysts using different systems and tools.

ETL 139

ETL Business Intelligence Big Data Architect Machine Learning 139

IBM Journey to AI blog

SEPTEMBER 25, 2023

Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively. The pursuit of hyperscale analytics The scale of Uber’s analytical endeavor requires careful selection of data platforms with high regard for limitless analytical processing.

Automation 256

Automation ETL Data Scientist Data Science 256

IBM Journey to AI blog

AUGUST 4, 2023

When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard. Then, it applies these insights to automate and orchestrate the data lifecycle.

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Machine Learning Metadata Automation AI 183