Precisely

FEBRUARY 14, 2023

Innovations like RPA may be the newest shiny objects, but their success is largely dependent on two things: the quality of the data that feeds automated processes, and the enrichment of this data to accelerate the automation process. If the data does validate the hail , the claim can be passed on to the next step in processing.

Data Quality 52

Data Quality Data Governance Algorithm AI 52

Precisely

MAY 4, 2023

Read the Report TDWI Checklist Report: Succeeding with Data Observability This report discusses five best practices for using observability tools to monitor, manage, and optimize operational data pipelines. It provides strategic guidance for enterprise data leaders in defining the core metrics of data quality and pipeline health.

Data Observability 52

Data Observability Data Quality Data Pipeline Machine Learning 52

Precisely

FEBRUARY 14, 2023

Innovations like RPA may be the newest shiny objects, but their success is largely dependent on two things: the quality of the data that feeds automated processes, and the enrichment of this data to accelerate the automation process. If the data does validate the hail , the claim can be passed on to the next step in processing.

Data Quality 52

Data Quality Data Governance Algorithm AI 52

phData

OCTOBER 25, 2024

“Quality over Quantity” is a phrase we hear regularly in life, but when it comes to the world of data, we often fail to adhere to this rule. Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules.

Data Quality 52

Data Quality Data Pipeline Data Governance Database 52

Pickl AI

OCTOBER 18, 2023

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

Data Quality 52

Data Quality ML ML Machine Learning 52

Data Science Blog

JUNE 27, 2023

In this representation, there is a separate store for events within the speed layer and another store for data loaded during batch processing. The serving layer acts as a mediator, enabling subsequent applications to access the data. On the other hand, the real-time views provide immediate access to the most current data.

Big Data 130

Big Data Big Data Apache Kafka Database 130

IBM Journey to AI blog

NOVEMBER 21, 2023

Apache Kafka is a well-known open-source event store and stream processing platform and has grown to become the de facto standard for data streaming. A schema registry is essentially an agreement of the structure of your data within your Kafka environment. Provision an instance of Event Streams on IBM Cloud here.

Apache Kafka 116

Apache Kafka Clustering Data Quality Data Governance 116

Data Science Dojo

OCTOBER 9, 2023

However, collecting and labeling real-world data can be costly, time-consuming, and inaccurate. Synthetic data offers a solution to these challenges. Scalability: Easily generate synthetic data for large-scale projects. Accuracy: Synthetic data can match real data quality.

Machine Learning 195

Machine Learning Machine Learning Data Quality 195

Tableau

APRIL 12, 2021

With data discovery as an important part of the cataloging experience, we want you to get the most relevant search results when looking for databases and tables in Tableau Server or Online. Our customers love data quality warnings, so we’ve also added a new feature based on a popular request! Starting with Tableau 2021.1,

Data Quality 52

Data Quality Tableau Database 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

Data Quality 52

Data Quality ML ML AI 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

Data Quality 52

Data Quality ML ML AI 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

Data Quality 52

Data Quality ML ML AI 52

Dataconomy

SEPTEMBER 4, 2023

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Women in Big Data

APRIL 3, 2025

Key Takeaways from the Event Generative AI moves from POC to industrialization : Financial sector companies are now deploying generative AI solutions at scale, with a focus on security, ethics, and ROI.

Big Data 52

Big Data Big Data AI AI 52

Precisely

MARCH 3, 2025

Data quality and governance are critical. Without clean, governed data, automation efforts can be undermined, impacting your business outcomes and AI initiatives. Data and process automation used to be seen as luxury but those days are gone. The result?

Data Quality 59

Data Quality Artificial Intelligence Artificial Intelligence AI 59

Dataversity

JANUARY 26, 2024

As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount.

Internet of Things 142

Internet of Things Data Governance Data Quality 142

Data Science Dojo

SEPTEMBER 6, 2023

Defining Data Ownership: Assigning Custodianship Like a castle with appointed caretakers, data governance designates data owners responsible for different datasets. Data ownership extends beyond mere possession—it involves accountability for data quality, accuracy, and appropriate use.

Data Warehouse 195

Data Warehouse Data Governance Data Quality ETL 195

Precisely

JANUARY 17, 2023

As they do so, access to traditional and modern data sources is required. Poor data quality and information silos tend to emerge as early challenges. Customer data quality, for example, tends to erode very quickly as consumers experience various life changes.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

PyImageSearch

JANUARY 6, 2025

It stands out due to its unusually high or low value compared to the rest of the data, which can indicate that it’s an anomaly, error, or something noteworthy. measurement errors, data entry mistakes, or genuine but rare events). In quality control, an outlier could indicate a defect in a manufacturing process.

Python 112

Python Deep Learning Deep Learning Clustering 112

Dataversity

APRIL 30, 2021

The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. Events are data snap-shots of complex activity sourced from the web, customer systems, ERP transactions, social media, […].

Data Pipeline 98

Data Pipeline Data Warehouse Data Governance Data Quality 98

Pickl AI

FEBRUARY 17, 2025

Summary: Machine Learning’s key features include automation, which reduces human involvement, and scalability, which handles massive data. It uses predictive modelling to forecast future events and adaptiveness to improve with new data, plus generalization to analyse fresh data.

Machine Learning 52

Machine Learning Machine Learning Supervised Learning ML 52

ODSC - Open Data Science

DECEMBER 5, 2023

You can see our photos from the event here , and be sure to follow our YouTube for virtual highlights from the conference as well. Over in San Francisco, we had a keynote for each day of the event. Other Events Aside from networking events and all of our sessions, we had a few other special events. What’s next?

Data Science 98

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 98

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this case, we are developing a forecasting model, so there are two main steps to complete: Train the model to make predictions using historical data. Apply the trained model to make predictions of future events. Workflow A corresponds to preprocessing, data quality and feature attribution drift checks, inference, and postprocessing.

Machine Learning 136

Machine Learning Machine Learning ML ML 136

Data Science Connect

JULY 25, 2023

Harnessing Satellite and Remote Sensing Data The model integrates satellite and remote sensing data, enabling a comprehensive understanding of environmental factors that contribute to droughts. Ensuring data accessibility and collaboration among countries in the region is essential.

Data Scientist 100

Data Scientist Analytics Data Quality Analytics 100

Data Science Dojo

MARCH 18, 2024

Yet, despite these impressive capabilities, their limitations became more apparent when tasked with providing up-to-date information on global events or expert knowledge in specialized fields. The model might offer generic advice based on its training data but lacks depth or specificity – and, most importantly, accuracy.

Database 331

Database Natural Language Processing AI AI 331

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Smart Data Collective

OCTOBER 13, 2021

Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results. How does Data Virtualization manage data quality requirements? In forecasting future events.

Data Visualization 145

Data Visualization Big Data Big Data Predictive Analytics 145

AWS Machine Learning Blog

AUGUST 29, 2023

Batch inference The SageMaker batch inference pipeline runs on a schedule (via EventBridge) or based on an S3 event trigger as well. The batch inference pipeline includes steps for checking data quality against a baseline created by the training pipeline, as well as model quality (model performance) if ground truth labels are available.

AWS 91

AWS Data Scientist Data Quality Python 91

Smart Data Collective

JUNE 22, 2023

One such field is data labeling, where AI tools have emerged as indispensable assets. This process is important if you want to improve data quality especially for artificial intelligence purposes. This article will discuss the influence of artificial intelligence and machine learning in data labeling. trillion by 2032.

Machine Learning 111

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 111

Dataversity

JUNE 14, 2022

Online security has always been an area of concern; however, with recent global events, the world we now live in has become increasingly cloud-centric. We are living in turbulent times.

Data Governance 98

Data Governance Data Quality Cloud Data Artificial Intelligence 98

AWS Machine Learning Blog

DECEMBER 15, 2023

To learn more about how to use natural language to explore and prepare data, refer to Use natural language to explore and prepare data with a new capability of Amazon SageMaker Canvas. On the Analyses tab, choose Data Quality and Insights Report. Choose Preview model to ensure there are no data quality issues.

Machine Learning 116

Machine Learning Machine Learning AWS ML 116

AWS Machine Learning Blog

FEBRUARY 21, 2025

If the question was Whats the schedule for AWS events in December?, AWS usually announces the dates for their upcoming # re:Invent event around 6-9 months in advance. Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team.

AWS 120

AWS Natural Language Processing Machine Learning Machine Learning 120

Dataversity

JUNE 7, 2024

I was privileged to deliver a workshop at Enterprise Data World 2024. Publishing this review is a way to express my gratitude to the fantastic team at DATAVERSITY and Tony Shaw personally for organizing this prestigious live event.

Data Governance 75

Data Governance Data Quality 75

AWS Machine Learning Blog

OCTOBER 9, 2023

To do so, we must complete the following steps: Modify the columns data types. Create two event types: Click and Watch. If we want to use one of the Amazon Personalize streamlined video on demand domain recommenders, such as Top Picks for You , Click and Watch would be required event types. Drop the ratings column.

AWS 116

AWS Machine Learning Machine Learning Python 116

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

Heartbeat

JUNE 12, 2023

This monitoring requires robust data management and processing infrastructure. Data Velocity: High-velocity data streams can quickly overwhelm monitoring systems, leading to latency and performance issues. To monitor your model in production, you need to instrument it to log relevant metrics and events.

Machine Learning 98

Machine Learning Machine Learning ML ML 98

Precisely

OCTOBER 17, 2024

This year, our annual Data Integrity Summit, Trust ’24, was better than ever – and a big part of what made the event so exciting was our first-ever Data Integrity Awards ! Users lacked trust in the company’s data, and were spending more time checking and cleaning it than analyzing it for better insights and decision-making.

Data Governance 69

Data Governance Data Quality Artificial Intelligence Artificial Intelligence 69