Cloudera

NOVEMBER 13, 2024

We are excited to announce the acquisition of Octopai , a leading data lineage and catalog platform that provides data discovery and governance for enterprises to enhance their data-driven decision making.

Metadata 90

Metadata Management Data Governance Data-driven 90

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Testing and Data Observability. Download the 2021 DataOps Vendor Landscape here.

Testing 300

Testing Machine Learning Consulting Data Science 300

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

datapine

DECEMBER 11, 2019

“Software as a service” (SaaS) is becoming an increasingly viable choice for organizations looking for the accessibility and versatility of software solutions and online data analysis tools without the need to rely on installing and running applications on their own computer systems and data centers. Dispelling 3 Common SaaS Myths.

Software 314

Software Cost-Benefit Data-driven Data Processing 314

Data Virtualization

APRIL 10, 2025

To keep pace, public sector administrations must evolve just as quickly, to close the gap between what communities need and what governments deliver. Reading Time: 2 minutes Todays world is fast-moving and unpredictable. In this dynamic environment, time is everything.

Modeling 75

Modeling Data Integration Management Data Architecture 75

DataKitchen

SEPTEMBER 17, 2021

Below is our final post (5 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a data mesh decentralized architecture. We see a DataOps process hub like the DataKitchen Platform playing a central supporting role in successfully implementing a data mesh.

Testing 237

Testing Data Architecture Measurement Visualization 237

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

DataKitchen

NOVEMBER 18, 2021

For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Add all these facts together, and it paints a picture that something is amiss in the data world. . The top-line result was that 97% of data engineers are feeling burnout. .

Testing 246

Testing Data Governance Measurement Software 246

Cloudera

JANUARY 7, 2025

As enterprises navigate complex data-driven transformations, hybrid and multi-cloud models offer unmatched flexibility and resilience. Heres a deep dive into why and how enterprises master multi-cloud deployments to enhance their data and AI initiatives. The terms hybrid and multi-cloud are often used interchangeably.

Cost-Benefit 82

Cost-Benefit Optimization Data-driven Strategy 82

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

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Specific prompts seem to “unlock” training data. Generative AI Has a Plagiarism Problem ChatGPT, for example, doesn’t memorize its training data, per se. This is the basis of The New York Times lawsuit against OpenAI.

Modeling 317

Modeling Machine Learning Risk Advertising 317

O'Reilly on Data

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The results gave us insight into what our subscribers are paid, where they’re located, what industries they work for, what their concerns are, and what sorts of career development opportunities they’re pursuing.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

DataKitchen

AUGUST 13, 2021

Figure 1 shows the 15-year cycle from screening to government agency approval and phase IV trials. If a company can use data to identify compounds more quickly and accelerate the development process, it can monetize its drug pipeline more effectively. How can they handle schema drift or data verification?

Testing 246

Testing Dashboards Marketing Measurement 246

O'Reilly on Data

SEPTEMBER 11, 2018

If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows. Data, even “big data,” doesn’t stay in the same place: it wants to move. In Privacy in Context , Helen Nissenbaum connects data’s mobility to privacy and ethics. We give up our data all the time.

Advertising 242

Advertising Insurance Experimentation Strategy 242

datapine

JULY 1, 2020

“The goal is to turn data into information, and information into insight.” – Carly Fiorina, former executive, president, HP. Digital data is all around us. quintillion bytes of data every single day, with 90% of the world’s digital insights generated in the last two years alone, according to Forbes. click to enlarge**.

Reporting 260

Reporting Dashboards Cost-Benefit Visualization 260

Cloudera

JANUARY 9, 2025

A Name That Matches the Moment For years, Clouderas platform has helped the worlds most innovative organizations turn data into action. But over the years, data teams and data scientists overcame these hurdles and AI became an engine of real-world innovation. Thats why were moving from Cloudera Machine Learning to Cloudera AI.

Machine Learning 85

Machine Learning Enterprise Data-driven Modeling 85

datapine

MAY 31, 2022

1) What Is Cloud Computing? While “the cloud” is just a metaphor for the internet, cloud computing is what people are really talking about these days. What Is Cloud Computing? These servers are busy storing, managing, and processing data that enables users to expand or upgrade their infrastructure and retrieve files on demand.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

datapine

FEBRUARY 22, 2022

1) What Is A Business Intelligence Strategy? Over the past 5 years, big data and BI became more than just data science buzzwords. In response to this increasing need for data analytics, business intelligence software has flooded the market. What Is A Business Intelligence Strategy? Table of Contents.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

DataKitchen

AUGUST 5, 2021

In our last post, we summarized the thinking behind the data mesh design pattern. In this post (2 of 5), we will review some of the ideas behind data mesh, take a functional look at data mesh and discuss some of the challenges of decentralized enterprise architectures like data mesh. Data Mesh Architecture Example.

Enterprise 246

Enterprise Management Data Processing Analytics 246

erwin

AUGUST 6, 2020

How Data Literacy Turns Data from a Burden to a Benefit. Today, data literacy is more important than ever. Data is now being used to support business decisions few executives thought they’d be making even six months ago. So, what is data literacy? What Is Data Literacy?

Contextual Data 135

Contextual Data Data Governance Metadata Digital Transformation 135

O'Reilly on Data

NOVEMBER 28, 2023

We wanted to find out what people are actually doing, so in September we surveyed O’Reilly’s users. Our survey focused on how companies use generative AI, what bottlenecks they see in adoption, and what skills gaps need to be addressed. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills.

Enterprise 339

Enterprise Modeling Testing Reporting 339

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

FEBRUARY 1, 2021

DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. These benefits are hugely important for data professionals, but if you made a pitch like this to a typical executive, you probably wouldn’t generate much enthusiasm. Find Unhappy Analytics Users.

Business Objectives 245

Business Objectives Cost-Benefit Measurement Metrics 245

datapine

SEPTEMBER 16, 2022

Previously, we discussed the top 19 big data books you need to read, followed by our rundown of the world’s top business intelligence books as well as our list of the best SQL books for beginners and intermediates. Data visualization, or ‘data viz’ as it’s commonly known, is the graphic presentation of data.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

DataKitchen

APRIL 28, 2021

Industry analysts who follow the data and analytics industry tell DataKitchen that they are receiving inquiries about “data fabrics” from enterprise clients on a near-daily basis. Gartner included data fabrics in their top ten trends for data and analytics in 2019. What is a Data Fabric?

Statistics 246

Statistics Optimization Data Analytics Technology 246

Cloudera

DECEMBER 4, 2024

Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. What is the Cloudera AI Inference service? Teams can analyze the data using any BI tool for model monitoring and governance purposes.

Metrics 73

Metrics Data Processing Machine Learning Deep Learning 73

erwin

OCTOBER 8, 2020

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way. Automated Cloud Migration.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

DataKitchen

MAY 10, 2021

As organizations strive to become more data-driven, Forrester recommends 5 actions to take to move from one stage of insights-driven business maturity to another. . Beginners: Ensure that your methodology, governance, and operations processes are agile and adaptive. . Blog: What is DataOps ? Forrester recommends: .

Data-driven 130

Data-driven Data Architecture Machine Learning Strategy 130

Domino Data Lab

AUGUST 6, 2021

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. As such, model governance needs to be applied to each model for as long as it’s being used. What Is Model Governance? What Is Model Governance? Purpose of Model Governance and Why It’s Important.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. The modern world is changing more and more quickly with each passing year. The solution? To keep abreast of current changes – at least at a level of basic understanding.

Technology 279

Technology Internet of Things IT IoT 279

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Data Lineage Tells an Important Origin Story. Who are the data owners?

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

DataKitchen

NOVEMBER 4, 2021

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

datapine

MARCH 25, 2019

In our data-rich age, understanding how to analyze and extract true meaning from the digital insights available to our business is one of the primary drivers of success. Despite the colossal volume of data we create every day, a mere 0.5% is actually analyzed and used for data discovery , improvement, and intelligence.

Key Performance Indicator 217

Key Performance Indicator Statistics Big Data Visualization 217

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

MAY 20, 2020

Data governance (DG) as a an “emergency service” may be one critical lesson learned coming out of the COVID-19 crisis. Organizations need to understand what the most critical operational activities are and the most impactful projects that need to proceed. Deploying a Data Governance Strategy.

Data Governance 144

Data Governance Metadata Risk Strategy 144

DataKitchen

DECEMBER 6, 2022

The document they wrote is exceptionally close to what we see in the market and what our products do ! This document is essential because buyers look to Gartner for advice on what to do and how to buy IT software. The two things we are most excited about are: First, DataOps is distinct from all Data Analytic tools.

Software 130

Software Marketing Data Lake Testing 130

erwin

FEBRUARY 6, 2020

As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. One piece of the research that stuck with me is that 70% of respondents spend 10 or more hours per week on data-related activities.

Management 144

Management Data Governance Cost-Benefit Metadata 144