IBM Journey to AI blog

APRIL 15, 2024

Data integration stands as a critical first step in constructing any artificial intelligence (AI) application. While various methods exist for starting this process, organizations accelerate the application development and deployment process through data virtualization. Why choose data virtualization?

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 225

Machine Learning Automation AI AI 225

Pickl AI

APRIL 14, 2023

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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Data Platform Data Integration Data Ingestion Automation 52

AWS Machine Learning Blog

JUNE 18, 2024

This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. She holds 30+ patents and has co-authored 100+ journal/conference papers.

Generative AI 131

Generative AI Data Ingestion Python LLM 131

IBM Journey to AI blog

JUNE 12, 2023

A long-standing partnership between IBM Human Resources and IBM Global Chief Data Office (GCDO) aided in the recent creation of Workforce 360 (Wf360), a workforce planning solution using IBM’s Cognitive Enterprise Data Platform (CEDP). Data quality is a key component for trusted talent insights.

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Data Quality Automation Data Ingestion Data Platform 187

Unite.AI

OCTOBER 14, 2024

Skip Levens is a product leader and AI strategist at Quantum, a leader in data management solutions for AI and unstructured data. The company’s approach allows businesses to efficiently handle data growth while ensuring security and flexibility throughout the data lifecycle.

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ML Data Ingestion Data Analysis Machine Learning 195

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Data Quality Metadata ETL Big Data 130

AWS Machine Learning Blog

AUGUST 4, 2023

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. We’re excited to announce Amazon SageMaker and Salesforce Data Cloud integration. The inference endpoints are connected with Data Cloud to drive predictions in real time.

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Data Scientist ML ETL AI 97

Unite.AI

FEBRUARY 21, 2024

Julian LaNeve is the Chief Technical Officer (CTO) at Astronomer , the driving force behind Apache Airflow and modern data orchestration to power everything from AI to general analytics. Julian does product and engineering at Astronomer where he focuses on developer experience, data observability, and AI.

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LLM Data Platform Software Engineer Chatbots 147

Marktechpost

JUNE 5, 2024

You can optimize your costs by using data profiling to find any problems with data quality and content. Fixing poor data quality might otherwise cost a lot of money. The 18 best data profiling tools are listed below. It comes with an Informatica Data Explorer function to meet your data profiling requirements.

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Data Quality Metadata Data Integration ETL 110

Towards AI

JANUARY 28, 2024

Last Updated on January 29, 2024 by Editorial Team Author(s): Cassidy Hilton Originally published on Towards AI. Recapping the Cloud Amplifier and Snowflake Demo The combined power of Snowflake and Domo’s Cloud Amplifier is the best-kept secret in data management right now — and we’re reaching new heights every day.

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ETL Python Data Platform Data Integration 111

Unite.AI

JUNE 4, 2024

However, the risk is not significant given Google Cloud's growth, broad data and infrastructure product portfolio and investment in Gen AI. A deep understanding of the cloud platform. We know Google Cloud inside and out, including key areas like data cloud, machine learning, AI, and Kubernetes.

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Data Ingestion Data Platform Machine Learning Generative AI 130

Unite.AI

DECEMBER 13, 2024

However, this data has remained largely underutilized. Yanoljas commitment to leveraging AI and advanced data platforms to improve these experiences was inspiring. Second, data is the foundation of AI. At Yanolja, we prioritize data integrity across the entire travel value chain.

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Software Engineer Data Quality Data Platform Automation 100

Marktechpost

NOVEMBER 19, 2024

Flexible Structure: Big Data systems can manage unstructured, semi-structured, and structured data without enforcing a strict structure, in contrast to data warehouses that adhere to structured schemas.

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Big Data ETL Business Intelligence Data Analysis 80

Pickl AI

OCTOBER 10, 2024

Introduction Data transformation plays a crucial role in data processing by ensuring that raw data is properly structured and optimised for analysis. Data transformation tools simplify this process by automating data manipulation, making it more efficient and reducing errors.

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ETL Data Quality Business Intelligence Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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Data Ingestion Metadata NLP Data Scientist 117

Marktechpost

JULY 18, 2023

ETL solutions employ several data management strategies to automate the extraction, transformation, and loading (ETL) process, reducing errors and speeding up data integration. Skyvia Skyvia is a cloud data platform created by Devart that enables no-coding data integration, backup, management, and access.

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ETL Data Integration Business Intelligence Automation 52

Pickl AI

DECEMBER 16, 2024

The objective is to guide businesses, Data Analysts, and decision-makers in choosing the right tool for their needs. Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals.

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ETL Data Ingestion Data Integration Machine Learning 52

Marktechpost

JULY 17, 2023

AI picks up knowledge by acquiring it, then applies it to new judgments. By teaching computers to reply just as well as—or better than—humans, artificial intelligence (AI) aims to identify the best answer. It relates to employing algorithms to find and examine data patterns to forecast future events.

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Machine Learning Data Mining Data Scientist Data Science 98

The MLOps Blog

MARCH 15, 2023

Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Data Consumption : You have reached a point where the data is ready for consumption for AI, BI & other analytics. Provides data security using AI & blockchain technologies.

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ETL Categorization Data Integration Automation 59

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.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52

Pickl AI

JUNE 23, 2023

In the world of artificial intelligence (AI), data plays a crucial role. It is the lifeblood that fuels AI algorithms and enables machines to learn and make intelligent decisions. And to effectively harness the power of data, organizations are adopting data-centric architectures in AI. text, images, videos).

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Continuous Learning Data Quality AI AI 52

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

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ETL Data Quality Data Integration Big Data 52

Marktechpost

JULY 17, 2023

It is impossible to completely substitute accurate data because precise, accurate data are still needed to generate practical synthetic examples of the information. How Important Is Synthetic Data? AI models are typically more accurate when they have more varied training data.

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

Pickl AI

APRIL 26, 2024

During a data analysis project, I encountered a significant data discrepancy that threatened the accuracy of our analysis. I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity.

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Data Analysis Machine Learning ETL Explainability 52

Pickl AI

JUNE 18, 2023

Aside from cluster management, responsibilities like data integration and data quality control can be difficult for organisations that use Hadoop systems. While all of its elements can now be found in stored in the cloud big data platforms, Hadoop remains largely an on-site solution form.

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Big Data Machine Learning Data Quality Data Analysis 52

Pickl AI

NOVEMBER 5, 2024

Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms. Users can connect to live data or extract data for analysis, giving flexibility to those with extensive and complex datasets. Tableau+: An AI-powered analytics package is available on Tableau Cloud.

Business Intelligence 52

Business Intelligence Data Analysis Data Extraction Big Data 52

Artificial Corner

JUNE 6, 2023

Uncover the evolution of data engineering, from storage to real-time processing and AI integration. Then, we will dive deep into how real-time processing and AI integration have revolutionized data pipelines, empowering advanced analytics, intelligent applications, and data-driven decision-making.

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Data Mining Big Data ETL Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

If you’re just faking it like a lot of Chat GPT and Gen AI folks are – faking it with no substance – people can’t connect. They started off as doing data integrations, and then became the ML monitoring team. You have to be interested in the problems, the people, and the solutions around you. People can connect with that.

ML 52

ML Data Scientist Machine Learning Data Science 52

Unite.AI

JANUARY 22, 2025

Coming from those two backgrounds, it was very clear to me that the data and compute challenges were converging as the industry was moving towards more advanced applications powered by data and AI. Auto generation: Integration and GenAI are both hard.

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Auto-complete Automation Machine Learning Data Integration 147

Marktechpost

NOVEMBER 1, 2024

The development of Artificial Intelligence (AI) tools has transformed data processing, analysis, and visualization, increasing the efficiency and insight of data analysts’ work. With so many alternatives, selecting the best AI tools can allow for deeper data research and greatly increase productivity.

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Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 96

Pickl AI

JUNE 11, 2024

Let’s explore some key features and capabilities that empower data warehouses to transform raw data into actionable intelligence: Historical Data Integration Imagine having a single, unified platform that consolidates data from all corners of your organization – sales figures, customer interactions, marketing campaigns, and more.

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ETL Data Mining Data Integration Actionable Intelligence 52

IBM Journey to AI blog

AUGUST 4, 2023

It’s often described as a way to simply increase data access, but the transition is about far more than that. 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.

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Machine Learning Metadata Automation AI 183

AWS Machine Learning Blog

DECEMBER 11, 2024

In this post, we illustrate the importance of generative AI in the collaboration between Tealium and the AWS Generative AI Innovation Center (GenAIIC) team by automating the following: Evaluating the retriever and the generated answer of a RAG system based on the Ragas Repository powered by Amazon Bedrock.

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Generative AI Chatbots Prompt Engineer Prompt Engineering 80