AWS Big Data

OCTOBER 29, 2024

To achieve this, they aimed to break down data silos and centralize data from various business units and countries into the BMW Cloud Data Hub (CDH). However, the initial version of CDH supported only coarse-grained access control to entire data assets, and hence it was not possible to scope access to data asset subsets.

Data Lake 109

Data Lake Sales Metadata Machine Learning 109

DataKitchen

DECEMBER 13, 2021

Without further ado, here are DataKitchen’s top ten blog posts, top five white papers, and top five webinars from 2021. Top 10 Blog Posts. Gartner – Top Trends and Data & Analytics for 2021: XOps. What is a Data Mesh? DataOps Data Architecture. DataOps is Not Just a DAG for Data.

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Data Architecture Data Governance Testing Modeling 246

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

DataKitchen

DECEMBER 7, 2021

Back by popular demand, we’ve updated our data nerd Gift Giving Guide to cap off 2021. We’ve kept some classics and added some new titles that are sure to put a smile on your data nerd’s face. Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, by Randy Bean.

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Data-driven Data Governance Big Data Data Science 246

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

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.

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Testing Data Architecture Measurement Visualization 237

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. . Data engineers end up fixing the same problem over and over.

Testing 246

Testing Data Governance Measurement Software 246

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

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

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

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

AWS Big Data

DECEMBER 19, 2024

Organizational data is often fragmented across multiple lines of business, leading to inconsistent and sometimes duplicate datasets. This fragmentation can delay decision-making and erode trust in available data. This solution enhances governance and simplifies access to unstructured data assets across the organization.

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Publishing Unstructured Data Metadata Data-driven 97

Data Virtualization

MARCH 28, 2024

As noted in the Gartner Hype Cycle for Finance Data and Analytics Governance, 2023, “Through. The post My Understanding of the Gartner® Hype Cycle™ for Finance Data and Analytics Governance, 2023 appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Finance 69

Finance Digital Transformation Analytics Data Integration 69

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 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

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

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.

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Reporting Dashboards Cost-Benefit Visualization 260

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.

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Visualization Dashboards Data-driven Statistics 304

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

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

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

DataKitchen

SEPTEMBER 20, 2021

Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. DataOps can and should be implemented in small steps that complement and build upon existing workflows and data pipelines. Figure 1: The four phases of Lean DataOps.

Testing 246

Testing Metrics Measurement Dashboards 246

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

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

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. 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.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

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.

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Data Quality Metrics Data-driven Management 241

DataKitchen

JANUARY 2, 2021

ModelOps is “ at the core of an organization’s AI strategy ” and is “ focused on operationalizing AI models, including the full life cycle management of AI decision models and AI governance.” ModelOps depends on a comprehensive data foundation enabled by data engineering practices and DataOps. White Paper: Governance as Code.

Testing 130

Testing Machine Learning Reporting Modeling 130

datapine

MAY 31, 2022

It provides better data storage, data security, flexibility, improved organizational visibility, smoother processes, extra data intelligence, increased collaboration between employees, and changes the workflow of small businesses and large enterprises to help them make better decisions while decreasing costs.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

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 ?

Data-driven 130

Data-driven Data Architecture Machine Learning Strategy 130

Cloudera

DECEMBER 17, 2024

Because data management is a key variable for overcoming these challenges, carriers are turning to hybrid cloud solutions, which provide the flexibility and scalability needed to adapt to the evolving landscape 5G enables. Cost is also a constant concern, especially as carriers work to scale their infrastructure to support 5G networks.

Enterprise 62

Enterprise Data Architecture Data-driven Optimization 62

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 average salary for data and AI professionals who responded to the survey was $146,000. The results then provide a place to start thinking about what effect the pandemic had on employment. Executive Summary. Demographics.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

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. Visual analytics: Around three million images are uploaded to social media every single day. The modern world is changing more and more quickly with each passing year.

Technology 279

Technology Internet of Things IT IoT 279

AWS Big Data

DECEMBER 4, 2024

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. We find it helpful to think of data operations as a factory. Most organizations run the data factory using manual labor. Figure 1: Ford assembly line, 1913.

Testing 152

Testing Dashboards Measurement Experimentation 152

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

DataKitchen

MAY 10, 2021

Data errors impact decision-making. When analytics and dashboards are inaccurate, business leaders may not be able to solve problems and pursue opportunities. Data errors infringe on work-life balance. Data errors also affect careers. Data sources must deliver error-free data on time.

Testing 214

Testing Manufacturing Data Quality Statistics 214

DataKitchen

JANUARY 5, 2021

Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Data Science Workflow – Kubeflow, Python, R. Data Engineering Workflow – Airflow, ETL.

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Testing Data Governance Metadata Visualization 147