CIO Business Intelligence

APRIL 8, 2025

Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

MARCH 25, 2025

These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities? Types of data debt include dark data, duplicate records, and data that hasnt been integrated with master data sources.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smart Data Collective

APRIL 20, 2022

Companies that utilize data analytics to make the most of their business model will have an easier time succeeding with Amazon. One of the best ways to create a profitable business model with Amazon involves using data analytics to optimize your PPC marketing strategy. However, it is important to make sure the data is reliable.

Data Quality 128

Data Quality Analytics Testing Sales 128

CIO Business Intelligence

JANUARY 7, 2025

Organizations will always be transforming , whether driven by growth opportunities, a pandemic forcing remote work, a recession prioritizing automation efficiencies, and now how agentic AI is transforming the future of work.

Digital Transformation 143

Digital Transformation Experimentation Cost-Benefit Strategy 143

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?

Machine Learning 364

Machine Learning Statistics Data Quality Modeling 364

DataKitchen

JANUARY 25, 2022

Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. When internal resources fall short, companies outsource data engineering and analytics. There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. .

Consulting 244

Consulting Testing Data Lake Data Quality 244

Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. These changes may include requirements drift, data drift, model drift, or concept drift. I suggest that the simplest business strategy starts with answering three basic questions: What?

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

FEBRUARY 6, 2025

As someone deeply involved in shaping data strategy, governance and analytics for organizations, Im constantly working on everything from defining data vision to building high-performing data teams. My work centers around enabling businesses to leverage data for better decision-making and driving impactful change.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. Discover the available data sources.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

datapine

JANUARY 24, 2021

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. Your Chance: Want to perform advanced data analysis with a few clicks? Data Is Only As Good As The Questions You Ask.

IT 317

IT Statistics KPI Data-driven 317

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. 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.

Machine Learning 279

Machine Learning Software Metadata Testing 279

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Data team morale is consistent with DataKitchen’s own research. We surveyed 600 data engineers , including 100 managers, to understand how they are faring and feeling about the work that they are doing.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

O'Reilly on Data

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3%

Enterprise 342

Enterprise Testing Modeling Reporting 342

Octopai

JULY 11, 2022

BAAAAAAAAD data. Okay, maybe “less-than-stellar-quality” data, if you want to be PC about it. But you see the “way-less-than-stellar” impact this data is having on your ostensibly data-driven organization. Tie data quality directly to business objectives. Better data quality?

Data Quality 98

Data Quality Strategy Business Objectives Sales 98

DataKitchen

APRIL 26, 2021

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.

Measurement 246

Measurement Metrics Data-driven Dashboards 246

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Data parity can help build confidence and trust with business users on the quality of migrated data.

Data Quality 96

Data Quality Data Lake Data Warehouse Metrics 96

CIO Business Intelligence

FEBRUARY 26, 2025

We actually started our AI journey using agents almost right out of the gate, says Gary Kotovets, chief data and analytics officer at Dun & Bradstreet. In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance.

IT 141

IT Enterprise Interactive Data Quality 141

O'Reilly on Data

OCTOBER 13, 2020

In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing. From a technical perspective, it is entirely possible for ML systems to function on wildly different data. Debugging AI Products. Proper AI product monitoring is essential to this outcome.

Management 314

Management Machine Learning Metrics Modeling 314

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

NOVEMBER 22, 2024

At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.

Data Lake 84

Data Lake Data Warehouse Cost-Benefit Data Transformation 84

CIO Business Intelligence

DECEMBER 11, 2024

In todays economy, as the saying goes, data is the new gold a valuable asset from a financial standpoint. A similar transformation has occurred with data. More than 20 years ago, data within organizations was like scattered rocks on early Earth.

Management 111

Management Data Governance Data Science Reporting 111

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Metrics 124

Metrics Testing Data Quality Dashboards 124

Wayne Yaddow

MARCH 3, 2025

These strategies can prevent delayed discovery of quality issues during data observability monitoring in production. Below is a summary of recommendations for proactively identifying and fixing flaws before they impact production data. Helps maintain business rule consistency and avoid regressions in data quality overtime.

Data Quality 52

Data Quality Strategy ROI Testing 52

DataKitchen

JUNE 7, 2021

This is a common question that we hear from our conversations with data scientists, engineers and analysts. DataOps includes four key objectives: Measure Your Process – As data professionals, we advocate for the benefits of data-driven decision making. What can you do? How can one get started given these limitations?

Testing 130

Testing IT Data-driven Measurement 130

DataKitchen

MARCH 5, 2024

Why Not Hearing About Data Errors Should Worry Your Data Team In the chaotic lives of data & analytics teams, a day without hearing of any data-related errors is a blessing. This creates an imbalance in workload and resource allocation and prevents a holistic view of data system health and efficiency.

Data Quality 146

Data Quality Measurement Testing Data-driven 146

DataKitchen

MARCH 12, 2024

Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software Lowering Serious Production Errors Key Benefit Errors in production can come from many sources – poor data, problems in the production process, being late, or infrastructure problems. Director, Data Analytics Team “We had some data issues.

Metrics 117

Metrics Software Cost-Benefit Testing 117

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataKitchen

FEBRUARY 23, 2024

DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps Data (and Analytic) Observability & Data Journey – Ideas and Background Data Journey Manifesto and Why the Data Journey Manifesto?

Testing 117

Testing Data-driven Data Quality Metrics 117

DataKitchen

OCTOBER 20, 2023

In today’s data-driven landscape, Data and Analytics Teams i ncreasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability. Data Observability platforms often need to deliver this level of customization.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

Wayne Yaddow

FEBRUARY 18, 2025

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

CIO Business Intelligence

FEBRUARY 20, 2025

Making decisions based on data To ensure that the best people end up in management positions and diverse teams are created, HR managers should rely on well-founded criteria, and big data and analytics provide these. Kastrati Nagarro The problem is that many companies still make little use of their data.

Big Data 84

Big Data Measurement Visualization Reporting 84

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

Data Quality 117

Data Quality Unstructured Data Testing Data-driven 117

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 363

Management Machine Learning Experimentation Metrics 363

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Then you build a massive data store that you can query for data to analyze. They also reveal things that starting to become scary (Privacy! EU Cookies!)

Modeling 125

Modeling Metrics Data Quality Data-driven 125

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity? Data integrity risks.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101