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

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. .

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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

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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DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

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Machine Learning Data-driven Optimization Data Analytics 130

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?

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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. It is a critical feature for delivering unified access to data in distributed, multi-engine architectures.

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Metadata Data Lake Dashboards Interactive 84

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. At the other end of the extreme consider a search engine.

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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.

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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. production).

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Octopai

JANUARY 31, 2021

Data lineage is an essential tool that among other benefits, can transform insights, help BI teams understand the root cause of an issue, as well as help achieve and maintain compliance. Through the use of data lineage, companies can better understand their data and its journey. Data Engineering Podcast.

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Data Governance Data Processing Data Quality Metadata 83

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. Most organizations run the data factory using manual labor. Too many data organizations run data operations like a hundred-year-old car factory.

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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. Then you must bulk load the legacy data.

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Data Governance Metadata Testing Data Lake 145

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.

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erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan.

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Data Governance Modeling Metadata Unstructured Data 144

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. Security issues.

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Risk Cost-Benefit Business Intelligence Data-driven 237

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

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.

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Data Governance Metadata Cost-Benefit Digital Transformation 145

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

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Deep Learning Machine Learning Modeling Software 143

erwin

JULY 22, 2020

Fostering organizational support for a data-driven culture might require a change in the organization’s culture. Recently, I co-hosted a webinar with our client E.ON , a global energy company that reinvented how it conducts business from branding to customer engagement – with data as the conduit. As an example, E.ON

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Data-driven Data Governance Digital Transformation Data Processing 136

Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . CDP data lifecycle integration and SDX security and governance. Easy job deployment.

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Enterprise Visualization Testing Management 127

erwin

MAY 22, 2025

As SAP PowerDesigner approaches its end of life (EOL), you could soon find yourself plunged into data modeling darkness. The updates are stopping, support is disappearing and connectivity is limited. Discontinued support When issues arise, youll have nowhere to turn for help.

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Modeling Uncertainty Metadata Data Integration 52

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

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

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Manufacturing Data Warehouse Sales Predictive Analytics 118

Cloudera

NOVEMBER 19, 2020

November 15-21 marks International Fraud Awareness Week – but for many in government, that’s every week. From bogus benefits claims to fraudulent network activity, fraud in all its forms represents a significant threat to government at all levels. The Public Sector data challenge. Modernization has been a boon to government.

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Machine Learning Data-driven Modeling Deep Learning 119

Cloudera

DECEMBER 11, 2020

In a previous blog post on CDW performance, we compared Azure HDInsight to CDW. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 with support for ACID transactions.

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Data Warehouse Metadata Machine Learning Measurement 110

Alation

JULY 15, 2021

Many data catalog initiatives fail. According to the latest report from Eckerson Group, Deep Dive on Data Catalogs , shoppers must match the goals of their organizations to the capabilities of their chosen catalog. A data catalog’s approach is key. Finding a trustworthy asset in a sea of data can take analysts months.

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Reporting Data Governance Recreation/Entertainment Metadata 98

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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DataKitchen

MAY 10, 2021

Data errors impact decision-making. Data errors infringe on work-life balance. Data errors also affect careers. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics.

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Testing Manufacturing Data Quality Statistics 214

Cloudera

MAY 10, 2024

Iceberg, a high-performance open-source format for huge analytic tables, delivers the reliability and simplicity of SQL tables to big data while allowing for multiple engines like Spark, Flink, Trino, Presto, Hive, and Impala to work with the same tables, all at the same time.

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Data Architecture Data Governance Big Data Marketing 103

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

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Metadata Snapshot Data Lake Metrics 126

Cloudera

SEPTEMBER 14, 2020

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Fundamental principles to be successful with Cloud data management. Or so they all claim.

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Management Cost-Benefit Manufacturing Machine Learning 111

Alation

FEBRUARY 18, 2021

Alation increases search relevancy with data domains, adds new data governance capabilities, and speeds up time-to-insight with an Open Connector Framework SDK. Categorize data by domain. As a data consumer, sometimes you just want data in a single category. Data quality is essential to data governance.

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Data Governance Data Quality Visualization Marketing 98

Smart Data Collective

NOVEMBER 20, 2022

We have talked extensively about the benefits of data centers in the past. Many organizations are increasing their Big Data footprint and looking to data centers to help them grow. Global companies are projected to spend over $274 billion on big data this year and data cetners have played a role in this trend.

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Big Data Advertising Marketing Technology 122

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics.

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Data-driven Testing Data Warehouse Enterprise 113

Cloudera

OCTOBER 13, 2020

On September 24, 2019, Cloudera launched CDP Public Cloud (CDP-PC) as the first step in delivering the industry’s first Enterprise Data Cloud. CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data. That Was Then.

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Data Warehouse Machine Learning Visualization Data Lake 97

O'Reilly on Data

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Given the cost of equipping a data center with high-end GPUs, they probably won’t attempt to build their own infrastructure. Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3%

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Enterprise Testing Modeling Reporting 343