Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

Tableau 102

Tableau Data Quality Analytics Analytics 102

AWS Machine Learning Blog

AUGUST 15, 2024

When SageMaker Data Wrangler finishes importing, you can start transforming the dataset. After you import the dataset, you can first look at the Data Quality Insights Report to see recommendations from SageMaker Canvas on how to improve the data quality and therefore improve the model’s performance.

ML 124

ML ML Data Preparation AWS 124

Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

Tableau 98

Tableau Data Quality Analytics Analytics 98

AWS Machine Learning Blog

DECEMBER 11, 2024

Using the services built-in source connectors standardizes and simplifies the work needed to maintain data quality and manage the overall data lifecycle.

AWS 104

AWS Database AI AI 104

IBM Journey to AI blog

MAY 9, 2023

Data: the foundation of your foundation model Data quality matters. An AI model trained on biased or toxic data will naturally tend to produce biased or toxic outputs. When objectionable data is identified, we remove it, retrain the model, and repeat. Data curation is a task that’s never truly finished.

AI 139

AI AI Data Quality Data Lakes 139

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

AWS Machine Learning Blog

FEBRUARY 21, 2025

He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations. Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team.

AWS 121

AWS Natural Language Processing Machine Learning Machine Learning 121

IBM Journey to AI blog

AUGUST 4, 2023

It’s distributed both in the cloud and on-premises, allowing extensive use and movement across clouds, apps and networks, as well as stores of data at rest. An architecture designed for data democratization aims to be flexible, integrated, agile and secure to enable the use of data and artificial intelligence (AI) at scale.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. Data Lakes allow for flexible analysis.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

ODSC - Open Data Science

FEBRUARY 14, 2023

It also looks at solutions that make it easier for data teams to hire, manage, retain, and execute effectively using modern data tooling — all while gaining that sought-after efficiency. It also addresses the strategies and best practices for implementing a data mesh.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

IBM Journey to AI blog

JULY 27, 2023

Artificial intelligence is disrupting many different areas of business. Data quality strongly impacts the quality and usefulness of content produced by an AI model, underscoring the significance of addressing data challenges. A data lakehouse is a fit-for-purpose data store.

AI 69

AI AI Data Scientist Data Quality 69

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

AI 93

AI AI Data Scientist Data Governance 93

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. The right tool can significantly enhance efficiency, scalability, and data quality.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

ODSC - Open Data Science

OCTOBER 15, 2023

AI is quickly scaling through dozens of industries as companies, non-profits, and governments are discovering the power of artificial intelligence. Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. So, what are you waiting for?

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

ODSC - Open Data Science

OCTOBER 25, 2024

Building an Open, Governed Lakehouse with Apache Iceberg and Apache Polaris (Incubating) Yufei Gu | Senior Software Engineer | Snowflake In this session, you’ll explore how open-source table formats are revolutionizing data architectures by enabling the power and efficiency of data warehouses within data lakes.

AI 52

AI AI Data Scientist Data Lakes 52

ODSC - Open Data Science

JANUARY 30, 2024

REGISTER NOW Designing and implementing data infrastructure Data engineers are responsible for choosing and configuring the right tools and technologies to store, process, and analyze data. This might involve setting up databases, data lakes, and streaming platforms. Think of it as like being a data doctor.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JUNE 11, 2024

Self-Service Analytics User-friendly interfaces and self-service analytics tools empower business users to explore data independently without relying on IT departments. Clearly defining your objectives will guide critical decisions regarding data selection, modelling approaches, and reporting strategies.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 52

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93

AWS Database ETL AI 93

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

AI AI Data Lakes Database 52

Pickl AI

AUGUST 9, 2024

Data Lake vs. Data Warehouse Distinguishing between these two storage paradigms and understanding their use cases. Students should learn how data lake s can store raw data in its native format, while data warehouses are optimised for structured data.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

AWS Machine Learning Blog

NOVEMBER 15, 2023

Therefore, when the Principal team started tackling this project, they knew that ensuring the highest standard of data security such as regulatory compliance, data privacy, and data quality would be a non-negotiable, key requirement.

AWS 117

AWS Analytics Analytics ML 117

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52

AWS Machine Learning Blog

AUGUST 4, 2023

In the data flow view, you can now see a new node added to the visual graph. For more information on how you can use SageMaker Data Wrangler to create Data Quality and Insights Reports, refer to Get Insights On Data and Data Quality. SageMaker Data Wrangler offers over 300 built-in transformations.

ML 97

ML ML AWS AI 97

Pickl AI

OCTOBER 17, 2024

ETL facilitates Data Analytics by transforming raw data into meaningful insights, empowering businesses to uncover trends, track performance, and make strategic decisions. ETL also enhances data quality and consistency by performing necessary data cleansing and validation during the transformation stage.

ETL 52

ETL Data Warehouse SQL Data Quality 52

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

AI 52

AI AI Data Science Machine Learning 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

The MLOps Blog

MARCH 21, 2023

Olalekan said that most of the random people they talked to initially wanted a platform to handle data quality better, but after the survey, he found out that this was the fifth most crucial need. And when the platform automates the entire process, it’ll likely produce and deploy a bad-quality model.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lakes 52

Data Lakes Data Governance Data Warehouse Business Intelligence 52

AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

AWS 137

AWS ML ML AI 137

Flipboard

FEBRUARY 19, 2025

In the age of generative artificial intelligence (AI), data isnt just kingits the entire kingdom. Robust data processing pipeline A sophisticated data processing pipeline maintains Alfreds knowledge base and promotes high-quality responses.

AWS 81

AWS Cloud Computing Natural Language Processing Data Lakes 81

ODSC - Open Data Science

APRIL 25, 2025

They offer the ability to specify a schema, expected values, and even such things as data quality expectations. He has a passion for helping organizations understand the true potential of their data by working as a leader, architect, and builder. These specifications are kept close to the code and versioned with it.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52