DataKitchen

APRIL 18, 2024

Introducing DataKitchen’s Open Source Data Observability Software Today, we announce that we have open-sourced two complete, feature-rich products that solve the data observability problem: DataOps Observervability and DataOps TestGen. DataOps TestGen is the silent warrior that ensures the integrity of your data.

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DataKitchen

AUGUST 24, 2023

Since the first edition of the DataOps Cookbook in 2019, we have talked with thousands of companies about their struggles to deliver data-driven insight to their customers. They have built data and analytic systems with great hope of success. As an industry, we have a conceptual hole in how we think about data analytic systems.

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CIO Business Intelligence

APRIL 25, 2024

At Salesforce World Tour NYC today, Salesforce unveiled a new global ecosystem of technology and solution providers geared to help its customers leverage third-party data via secure, bidirectional zero-copy integrations with Salesforce Data Cloud. It works in Salesforce just like any other native Salesforce data,” Carlson said.

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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.

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Octopai

APRIL 20, 2023

Data mesh is an approach to data architecture that is intentionally distributed, where data is owned and governed by domain-specific teams who treat the data as a product to be consumed by other domain-specific teams. What are the principles behind data mesh architecture?

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erwin

FEBRUARY 28, 2024

At Sparkle, we’re a holistic data partner helping organizations increase their data maturity in a strategic yet pragmatic way. One of the key ingredients to ensure data is really embedded in an organization, and one of the key enablers to increase the strategic impact of data, is the setup of a successful data governance program.

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Metadata Data Governance Data Quality Technology 52

Alation

AUGUST 18, 2022

How do you approach data lineage? We all know that data lineage is a complex and challenging topic. In this blog, I am drilling into something I’ve been thinking about and studying for a long time: fundamental approaches to lineage creation and maintenance. What Is Data Lineage Creation & Maintenance?

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Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Plus, AI can also help find key insights encoded in data.

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DataKitchen

AUGUST 9, 2021

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. Source: Thoughtworks.

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Alation

FEBRUARY 7, 2023

There was a software product demo showcasing its ability to scan every layer of your application code, and I was intrigued to see how it worked. The product collected an impressive amount of metadata, from the user interface to the database structure. That was my earliest taste of data lineage. Or so I thought.

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Metadata Data Warehouse Visualization Data Quality 52

Octopai

MARCH 23, 2022

Dirty Meat… and Dirty Data. Mass production. But even though “dirty meat” is a small concern, “dirty data” is the scourge of any industry that relies heavily on information systems. While “dirty data” doesn’t sound as threatening as “dirty meat” (after all, it’s your computer ingesting it, not you), don’t be deceived.

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DataKitchen

DECEMBER 6, 2022

The document they wrote is exceptionally close to what we see in the market and what our products do ! The two things we are most excited about are: First, DataOps is distinct from all Data Analytic tools. Orchestration : Connectivity, workflow automation, lineage, scheduling, logging, troubleshooting, and alerting.

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Octopai

APRIL 20, 2023

Octopai has recently expanded its offerings by introducing unique and comprehensive DAX (Data Analysis Expressions) coverage support for Power BI, SSRS (SQL Server Reporting Services), and Tabular Analysis Services. To compute the sales performance metrics, DAX expressions are needed to aggregate the sales data based on different criteria.

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DataKitchen

MAY 4, 2023

Webinar Summary: DataOps and Data Mesh Chris Bergh, CEO of DataKitchen, delivered a webinar on two themes – Data Products and Data Mesh. Bergh started by discussing the complexity within data and analytics teams, stating that complexity makes everything more complicated and, in the long run, it kills productivity.

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AWS Big Data

FEBRUARY 27, 2024

In the ever-evolving world of finance and lending, the need for real-time, reliable, and centralized data has become paramount. Bluestone , a leading financial institution, embarked on a transformative journey to modernize its data infrastructure and transition to a data-driven organization.

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erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

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Metadata Data Governance Key Performance Indicator Data Quality 111

O'Reilly on Data

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). (You

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Jen Stirrup

MARCH 29, 2023

Despite technological advances, businesses still need help working with data. Data is complex, and companies often need to catch up on what they are trying to achieve. They are also starting to realize – and accept – that data is challenging. What does a sound, intelligent data foundation give you?

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Metadata Data Warehouse Data Integration Business Intelligence 120

DataKitchen

JULY 3, 2023

Data Journey First DataOps Putting Problems in Your Data Estate at the Forefront Welcome to the high-octane world of DataOps, a powerhouse that turbocharges data analytics development and management. But as we navigate ever-evolving seas of data, it’s high time we reset our course.

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Testing Risk Data-driven Statistics 130

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

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Metrics Data Quality Data Lake Statistics 82

Cloudera

MARCH 3, 2023

based nVizhen, a data consulting firm, I became a Cloudera partner. We implemented CDP (Cloudera Data Platform) for innovative G2k organizations so they could tackle transformational use cases and exact real-time insights. As a CDO, I need full data life cycle capability. When I joined L.A.-based First, fullness. Second, reach.

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Consulting Machine Learning Analytics IT 80

O'Reilly on Data

FEBRUARY 11, 2019

In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. Temporal data and time-series analytics. Deep Learning.

Big Data 209

Big Data Technology Machine Learning Deep Learning 209

Cloudera

AUGUST 3, 2021

Toyota weathered the early chip shortage well with agile and robust supply chains, only to be caught with final assembly production shortages due to consumers rushing to their once robust availability. . In summary, predicting future supply chain demands using last year’s data, just doesn’t work.

Analytics 107

Analytics Digital Transformation Risk Forecasting 107

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

IBM Big Data Hub

FEBRUARY 2, 2024

Almost a year ago, IBM encountered a data validation issue during one of our time-sensitive mergers and acquisitions data flows. That is when I discovered one of our recently acquired products, IBM® Databand® for data observability. IBM integrated Databand into our data flow, which comprised over 100 pipelines.

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Dashboards Statistics Machine Learning Enterprise 92

Cloudera

FEBRUARY 16, 2022

The complete list is shown below: Model Lineage . Machine Learning Model Lineage. Before we can understand how model lineage is managed and subsequently audited, we first need to understand some high-level constructs within CML. Within the CML data service, model lineage is managed and tracked at a project level by the SDX.

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Machine Learning Modeling Metadata Recreation/Entertainment 82

DataKitchen

JUNE 19, 2023

Our recent survey showed that 97% of data engineers report experiencing burnout in their day-to-day jobs. Given the complicated distributed systems we use to get value from data and the diversity of data, we need a simplifying framework. That idea is the Data Journey.

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Testing Cost-Benefit Metrics Data Quality 130

Domino Data Lab

AUGUST 6, 2021

This includes: Model lineage, from data acquisition to model building Model versions in production, as they are updated based on new data Model health in production with model monitoring principles Model usage and basic functionality in production Model costs. First is the data the model is using.

Machine Learning 145

Machine Learning Modeling Testing Risk 145

CIO Business Intelligence

APRIL 4, 2024

Leveraging expertise at software developer Palantir Technologies, Redmond’s team developed a model that consolidated and cleansed the data from those systems, then analyzed it to provide insights — and fairly sophisticated recommendations — to decision makers. It can be faster, more accurate, and make the teams more productive.”

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Enterprise Cost-Benefit Forecasting Strategy 129

Smarten

JANUARY 30, 2024

Self-Serve Data Preparation Transforms Business Users to Citizen Data Scientists! Data Scientists spend a lot of time gathering and preparing data for analysis, and that is time they could spend more productively performing tasks that add value and strategic direction. It’s simple.

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Analytics Data Quality Visualization Metadata 67

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.

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erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

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Metadata Data Governance Data Quality Data Warehouse 90

erwin

MARCH 25, 2021

erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, the second webinar focused on “ The Value of Data Governance & How to Quantify It.”.

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. This also diminishes the value of data as an asset.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

DataKitchen

AUGUST 13, 2021

If a company can use data to identify compounds more quickly and accelerate the development process, it can monetize its drug pipeline more effectively. DataOps automation provides a way to boost innovation and improve collaboration related to data in pharmaceutical research and development (R&D). Mastery of Heterogeneous Tools.

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Jen Stirrup

OCTOBER 28, 2019

The Microsoft Power BI team have released a preview Data Lineage feature and it is a good start for organizations who are starting to think about data management. The Power BI lineage view displays the lineage relationships between all the artifacts in a workspace, and all its external dependencies.

IT 85

IT Business Intelligence Data Governance ROI 85

Ontotext

FEBRUARY 12, 2024

Although the enterprise data landscape is littered with new data technology and offerings, the most pressing problem data teams face today isn’t a lack of technology or skills; it’s not knowing how to create a modern data experience. Why Data Mesh?

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