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.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Jet Global

DECEMBER 12, 2019

Since its initial release in 2016, Power BI has quickly become the talk of the town in business intelligence and analytics circles, and rightly so! Its data visualizations provide easily digestible insights into your business via robust, interactive dashboards. We’re lovers of all things data, and blogs about Power BI are no exception.

Visualization 59

Visualization Dashboards Interactive Consulting 59

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. That was amazing for the team.”

Metrics 120

Metrics Software Cost-Benefit Testing 120

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. IRM UK Connects.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

DataKitchen

APRIL 11, 2024

The hosted by Christopher Bergh with Gil Benghiat from DataKitchen covered a comprehensive range of topics centered around improving the performance and efficiency of data teams through Agile and DataOps methodologies. The goal is to reduce errors and operational overhead, allowing data teams to focus on delivering value.

Statistics 157

Statistics Manufacturing Data Processing Data Quality 157

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246

Analytics Sales Testing Cost-Benefit 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

MARCH 11, 2021

Gartner identified XOps (DataOps, ModelOps, DevOps) as one of the top trends in data and analytics for 2021. DataKitchen Blog: Why Are There So Many *Ops Terms? Figure 1: Ops terms can be organized by team and technical environment/process. DataKitchen White Paper: DataOps is NOT Just DevOps for Data. See Figure 1.

Analytics 130

Analytics Machine Learning Modeling Reporting 130

Cloudera

APRIL 23, 2024

The Hackathon was intended to provide data science experts with access to Cloudera machine learning to develop their own Accelerated Machine Learning Project (AMP) focused on solving one of the many environmental challenges facing the world today.

Machine Learning 84

Machine Learning Data Science Data Processing Data-driven 84

datapine

MARCH 6, 2023

Employee engagement refers to the level of commitment employees have to their work, their team’s goals, and their company’s mission. For this, you can use HR analytics software. Engaged employees understand their purpose and impact on the organization. But before you can improve something, you need to know where you stand.

Data-driven 234

Data-driven Reporting Interactive Statistics 234

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.

Testing 246

Testing Data Lake Metadata Publishing 246

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Or, as one of our customers put it, “How do I increase the total amount of team insight generated without continually adding more staff (and cost)?” Staff turnover, stress, and unhappiness. It’s not been going well.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

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 157

Testing Dashboards Measurement Experimentation 157

DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

DataKitchen

DECEMBER 6, 2022

The two things we are most excited about are: First, DataOps is distinct from all Data Analytic tools. As founders, we sat in a room eight years ago (when all the rage was Hadoop, data prep, and data lakes) and debated — will there ever be an ‘ops’ layer that sits next to all the current data tools?

Software 130

Software Marketing Data Lake Testing 130

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. www.erwin.com/blog/defining-data-governance/.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

DataKitchen

JANUARY 2, 2021

ModelOps depends on a comprehensive data foundation enabled by data engineering practices and DataOps. Blog: Deliver AI and ML Models at Scale with ModelOps. DataOps provides “ the foundational data operations for operationalizing AI models. Data-AI Role Alignment. Blog: Add DataOps Tests for Error-Free Analytics.

Testing 130

Testing Machine Learning Reporting Modeling 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. Being proactive rather than reactive in seeking out potential data errors can save your team from future blow-ups.

Data Quality 150

Data Quality Measurement Testing Data-driven 150

Cloudera

MARCH 6, 2024

As we enter into a new month, the Cloudera team is getting ready to head off to the Gartner Data & Analytics Summit in Orlando, Florida for one of the most important events of the year for Chief Data Analytics Officers (CDAOs) and the field of data and analytics.

Data Analytics 103

Data Analytics Analytics Snapshot Data Processing 103

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. . The following resources will help you understand DataOps principles and how to get started: Blog: For Data Team Success, What You Do is Less Important Than How You Do It.

Data-driven 130

Data-driven Data Architecture Machine Learning Strategy 130

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 176

Insurance Metadata Data-driven Data Quality 176

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

BA Learnings

JANUARY 23, 2024

Being a business analyst is a journey filled with challenges and triumphs, where the treasure is not just data but insights that transform businesses. Analytical Acumen: Seeing The Forest And The Trees As a BA, your analytical skills can be compared to a finely-tuned compass, guiding stakeholders through the forest of data.

Business Analysis 130

Business Analysis Uncertainty Reporting Management 130

datapine

JUNE 15, 2023

These analytical tools allow decision-makers to get a sense of their performance in a number of areas and extract valuable insights to inform their future strategies and boost growth. In the past, these reports were used after a month or even a year since the data being displayed was generated. What Is A Performance Report?

Reporting 207

Reporting Cost-Benefit Dashboards Sales 207

Cloudera

APRIL 18, 2024

All of that technology, though, depends on data to be successful. In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular.

Analytics 104

Analytics Metadata Data Strategy Optimization 104

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

DataKitchen

JANUARY 25, 2022

Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. The strategic value of analytics is widely recognized, but the turnaround time of analytics teams typically can’t support the decision-making needs of executives coping with fast-paced market conditions.

Consulting 244

Consulting Testing Data Lake Data Quality 244

IBM Big Data Hub

FEBRUARY 28, 2024

Sourcing teams are automating processes like data analysis as well as supplier relationship management and transaction management. This helps reduce errors to improve data quality and response times to questions, which improves customer and supplier satisfaction. Try out cognitive intelligence free for 30-days.

Strategy 105

Strategy Technology Cost-Benefit Risk Management 105

IBM Big Data Hub

APRIL 1, 2024

Stacking strong data management, predictive analytics and GenAI is foundational to taking your product organization to the next level. With IBM watsonx™ Assistant, companies can build large language models and train them using proprietary information, all while helping to ensure the security of their data.

Predictive Analytics 85

Predictive Analytics Sales Enterprise Predictive Modeling 85

Cloudera

DECEMBER 13, 2023

Implementing a cohesive data vision LGIM’s Global Chief Operating Office is responsible for the company’s technology, data, client servicing and the management of its strategic operating agenda. LGIM’s data ecosystem had become fragmented over time as it had grown.

Management 88

Management Technology Risk Optimization 88

CIO Business Intelligence

DECEMBER 12, 2022

Microsoft has signed a 10-year deal with the London Stock Exchange Group (LSEG) that calls for the software giant to buy a 4% stake in the exchange in order to jointly develop new products and services for data and analytics. billion) in 2021. billion on cloud-related products with Microsoft.

Manufacturing 111

Manufacturing Interactive Marketing Risk 111

Srividya Sridharan

APRIL 5, 2021

After a brief hiatus, the Insights Beat blog series is back, where I will continue to feature and curate the latest research and thought leadership from our business insights, data, analytics and AI research team.

Publishing 128

Publishing Data Analytics Analytics Data Governance 128

Dataiku

NOVEMBER 4, 2020

The bulk of an organization’s data science, machine learning, and AI conquests come down to improving decision-making capabilities. Teams may aim to achieve new levels of agility, expedite the time to insights, or refine the process leading up to the business value extraction so that it’s more efficient.

Prescriptive Analytics 145

Prescriptive Analytics Analytics Machine Learning Data Science 145

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. Particularly those on the “the create side of the house” who are tasked to deliver insights and analytics. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

IBM Big Data Hub

FEBRUARY 5, 2024

These foundation models, built on large language models, are trained on vast amounts of unstructured and external data. They can generate responses like text and images, while simultaneously interpreting and manipulating existing data. They require job plans and work instructions for asset failures and repairs.

Optimization 100

Optimization Management Key Performance Indicator Modeling 100

IBM Big Data Hub

MARCH 29, 2024

If you’re currently using traditional AI, advanced analytics, and intelligent automation, aren’t you already getting deep insights into asset performance? Challenge 1: Orchestrate relevant data The journey to generative AI begins with data management. Undoubtedly. But what if you could optimize even further?

Management 91

Management Structured Data Modeling Data Governance 91

IBM Big Data Hub

FEBRUARY 12, 2024

Recognizing the need to harness real-time data, businesses are increasingly turning to event-driven architecture (EDA) as a strategic approach to stay ahead of the curve. This trend grows stronger as organizations realize the benefits that come from the power of real-time data streaming. Do you remember playing in the sandbox as a kid?

Data-driven 86

Data-driven Cost-Benefit Uncertainty Technology 86