IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 186

Machine Learning Metadata Automation AI 186

AWS Machine Learning Blog

JUNE 18, 2024

The platform, although functional, deals with CSV and JSON files containing hundreds of thousands of rows from various manufacturers, demanding substantial effort for data ingestion. The objective is to automate data integration from various sensor manufacturers for Accra, Ghana, paving the way for scalability across West Africa.

Generative AI 132

Generative AI Data Ingestion Python LLM 132

AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

Data Scientist 95

Data Scientist ML ETL Data Platform 95

IBM Journey to AI blog

JULY 3, 2024

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

Data Quality 112

Data Quality Metadata Business Intelligence AI 112

Marktechpost

JUNE 5, 2024

Businesses that require assistance with managing or personalizing procedures related to huge data quality can use the company’s range of professional services and support offerings. Collibra Data Intelligence Platform Launched in 2008, Collibra offers corporate users data intelligence capabilities.

Data Quality 115

Data Quality Metadata Data Integration ETL 115

AWS Machine Learning Blog

MARCH 5, 2025

Scaling ground truth generation with a pipeline To automate ground truth generation, we provide a serverless batch pipeline architecture, shown in the following figure. The serverless batch pipeline architecture we presented offers a scalable solution for automating this process across large enterprise knowledge bases. 201% $12.2B

Generative AI 80

Generative AI LLM AI AI 80

Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning. These tools automate the process, making it faster and more accurate.

ETL 52

ETL Data Quality Machine Learning Business Intelligence 52

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

ETL 52

ETL Data Mining Data Integration Actionable Intelligence 52

The MLOps Blog

MARCH 15, 2023

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Let’s understand how the other aspects of a data pipeline help the organization achieve its various objectives.

ETL 59

ETL Categorization Data Integration Automation 59

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

ETL 52

ETL LLM Data Ingestion Automation 52

TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

ETL 52

ETL LLM Data Ingestion Automation 52

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. Data Activator : Automates workflows, making data-triggered actions possible.

ETL 52

ETL Data Ingestion Data Integration Machine Learning 52

ODSC - Open Data Science

OCTOBER 9, 2024

By automating repetitive tasks and generating boilerplate code, these tools free up time for engineers to focus on more complex, creative aspects of software development. Well, it is offering a way to automate the time-consuming process of writing and running tests. Just keep in mind, that this shouldn’t replace the human element.

Software Engineer 40

Software Engineer Software Development DevOps Machine Learning 40

The MLOps Blog

MAY 31, 2023

How to set up an ML Platform in eCommerce? The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. An ML Platform helps in the faster iteration of an ML project lifecycle. via Data Connectors.

ML 59

ML Algorithm Data Drift Machine Learning 59

The MLOps Blog

JANUARY 26, 2024

Keeping track of how exactly the incoming data (the feature pipeline’s input) has to be transformed and ensuring that each model receives the features precisely how it saw them during training is one of the hardest parts of architecting ML systems. One of the core principles of MLOps is automation. What is a feature store?

Machine Learning 72

Machine Learning Metadata ML Python 72

Artificial Corner

JUNE 6, 2023

Cloud-based data storage solutions, such as Amazon S3 (Simple Storage Service) and Google Cloud Storage, provide highly durable and scalable repositories for storing large volumes of data. These services automate infrastructure management tasks, allowing data engineers and scientists to focus on data processing and analysis.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 6, 2024

Experimenting with LLMs to automate fact generation from QA ground truth using LLMs can help. Automate, but verify, with LLMs – Use LLMs to generate initial ground truth answers and facts, with a human review and curation to align with the desired assistant output standards.

Generative AI 95

Generative AI LLM AI AI 95

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. Users can write data to managed RMS tables using Iceberg APIs, Amazon Redshift, or Zero-ETL ingestion from supported data sources.

Metadata 141

Metadata ETL Data Analysis Big Data 141