AWS Big Data

AUGUST 8, 2024

Thousands of organizations build data integration pipelines to extract and transform data. They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. After a few months, daily sales surpassed 2 million dollars, rendering the threshold obsolete.

Data Quality 112

Data Quality Statistics Visualization Metrics 112

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Science 300

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning. Data unification and integration.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 97

Data Quality Statistics Data Lake Visualization 97

Smart Data Collective

APRIL 30, 2021

However, your data integrity practices are just as vital. But what exactly is data integrity? How can data integrity be damaged? And why does data integrity matter? What is data integrity? Indeed, without data integrity, decision-making can be as good as guesswork.

Data Integration 122

Data Integration Strategy Software Management 122

CIO Business Intelligence

FEBRUARY 26, 2025

And in an October Gartner report, 33% of enterprise software applications will include agentic AI by 2033, up from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomously. Having clean and quality data is the most important part of the job, says Kotovets.

IT 141

IT Enterprise Interactive Data Quality 141

AWS Big Data

MAY 23, 2024

Hundreds of thousands of organizations build data integration pipelines to extract and transform data. They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. We also show how to take action based on the data quality results.

Data Quality 100

Data Quality Metrics Data Lake Sales 100

AWS Big Data

DECEMBER 4, 2024

Collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics with Amazon Q Developer , the most capable generative AI assistant for software development, helping you along the way. Having confidence in your data is key.

Data Analytics 85

Data Analytics Analytics Data Lake Data Quality 85

O'Reilly on Data

DECEMBER 19, 2018

In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure. Humans are still needed to write software, but that software is of a different type. Developers of Software 1.0

Machine Learning 279

Machine Learning Software Metadata Testing 279

Octopai

AUGUST 3, 2022

It’s also a critical trait for the data assets of your dreams. What is data with integrity? Data integrity is the extent to which you can rely on a given set of data for use in decision-making. Where can data integrity fall short? Too much or too little access to data systems.

Data Integration 98

Data Integration Manufacturing Data Quality Data Governance 98

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 82

Data Quality Data-driven Data Lake Metrics 82

David Menninger's Analyst Perspectives

OCTOBER 8, 2024

As I recently noted , the term “data intelligence” has been used by multiple providers across analytics and data for several years and is becoming more widespread as software providers respond to the need to provide enterprises with a holistic view of data production and consumption.

Data Quality 130

Data Quality Data Governance Enterprise Visualization 130

Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

Data Quality 64

Data Quality Analytics Machine Learning Visualization 64

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataKitchen

MAY 10, 2024

This blog post explores the challenges and solutions associated with data ingestion monitoring, focusing on the unique capabilities of DataKitchen’s Open Source Data Observability software. This process is critical as it ensures data quality from the onset. Have all the source files/data arrived on time?

Data Quality 130

Data Quality Testing Software Dashboards 130

DataKitchen

MAY 10, 2021

Some of the DataOps best practices and industry discussion around errors have coalesced around the term “data observability.” In modern IT and software dev, people use the term observability to include the ability to find the root cause of a problem. It’s not about data quality . It’s not only about the data.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? These discussions are a critical prerequisite for determining data usage, standards, and the business relevant metrics for measuring and improving data quality.

Data Quality 56

Data Quality Enterprise Business Intelligence Data Governance 56

Alation

AUGUST 9, 2022

But in the four years since it came into force, have companies reached their full potential for data integrity? But firstly, we need to look at how we define data integrity. What is data integrity? Many confuse data integrity with data quality. Is integrity a universal truth?

Data Integration 52

Data Integration Data Quality Measurement Data-driven 52

DataKitchen

AUGUST 16, 2024

2024 Gartner Market Guide To DataOps We at DataKitchen are thrilled to see the publication of the Gartner Market Guide to DataOps, a milestone in the evolution of this critical software category. At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data.

Marketing 124

Marketing Data Quality Testing Metadata 124

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Metrics 124

Metrics Testing Data Quality Dashboards 124

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Your data governance program needs to continually break down new siloes.

Data Governance 142

Data Governance Management Metadata Data Quality 142

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. Try our professional BI software for 14 days, completely free! Actually, it usually isn’t.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

erwin

DECEMBER 9, 2024

And if it isnt changing, its likely not being used within our organizations, so why would we use stagnant data to facilitate our use of AI? The key is understanding not IF, but HOW, our data fluctuates, and data observability can help us do just that. Tackle AI data readiness and governance with erwin.

Metadata 52

Metadata Data Quality Sales Modeling 52

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Random attacks: exposing models to high volumes of random input data and seeing how they react. Random attacks can reveal all kinds of unexpected software and math bugs.

Machine Learning 276

Machine Learning Modeling Testing Risk Management 276

CIO Business Intelligence

APRIL 29, 2022

This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. The shift away from ‘Software 1.0’ where applications have been based on hard-coded rules has begun and the ‘Software 2.0’ era is upon us. Addressing the Challenge.

Data Governance 145

Data Governance IT Data Lake Risk 145

CIO Business Intelligence

APRIL 17, 2024

Salesforce’s reported bid to acquire enterprise data management vendor Informatica could mean consolidation for the integration platform-as-a-service (iPaaS) market and a new revenue stream for Salesforce, according to analysts.

Cost-Benefit 128

Cost-Benefit B2B Marketing Enterprise 128

Smart Data Collective

OCTOBER 13, 2021

Data visualization is a concept that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that may go unnoticed in text-based data can be more easily exposed and recognized with data visualization software.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

DataKitchen

DECEMBER 9, 2022

DataOps automation typically involves the use of tools and technologies to automate the various steps of the data analytics and machine learning process, from data preparation and cleaning, to model training and deployment. Query> Is DataOps something that can be solved with software or is it more of a people process?

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

Grooper

MARCH 5, 2020

If your organization has any kind of data and analytics initiative, then chances are you have people – maybe even an entire department dedicated to managing and integrating data for (and between) software applications to achieve some sort of business outcome. Is a Power-User or a Data Scientist an Information Steward?

Data Lake 98

Data Lake Metadata Data Quality Software 98

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. For users that require a unified view of software quality, this is unacceptable.

Software 52

Software Data Lake Testing Cost-Benefit 52

CIO Business Intelligence

MAY 30, 2024

First, you can be a taker, by understanding the embedded capabilities that are being incorporated into existing software platforms you currently own and defining how you can leverage those for the organization. Talk to us about how leaders should be thinking about the role of data quality in terms of their AI deployments.

Data Quality 104

Data Quality Key Performance Indicator Digital Transformation Management 104

CIO Business Intelligence

JANUARY 24, 2024

Overlooking these data resources is a big mistake. The proper use of unstructured data will become of increasing importance to IT leaders,” says Kevin Miller, CTO of enterprise software developer IFS. “It Creating data silos Denying business users access to information because of data silos has been a problem for years.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

Andrew White

JUNE 11, 2019

Google acquires Looker – June 2019 (infrastructure/search/data broker vendor acquires analytics/BI). Salesforce closes acquisition of Mulesoft – May 2018 (business app vendor acquires data integration). Even the vast spend on software in D&A is centered on aspects of the two parts.

IT 82

IT Data Quality Data Integration Business Objectives 82

CIO Business Intelligence

JANUARY 9, 2024

“It is so easy to get excited by technology like AI, and people want to implement 100 different pilots and tests, but you have to focus on the ideas that will provide value to the organization,” says Juan Perez, CIO of software maker Salesforce. Can the current state of our data operations deliver the results we seek?

IT 140

IT Risk Cost-Benefit Machine Learning 140

AWS Big Data

FEBRUARY 29, 2024

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109