Juice Analytics

APRIL 6, 2021

At Juice, we are working everyday to create these habits and we wanted to share how we are building a data-first mindset and where we look for inspiration. Habit 1: Define shared metrics Data fluency requires getting everyone on the same page as to what matters most. How do we track “first success” for a user?

Metrics 119

Metrics Dashboards Data-driven Data Quality 119

Alation

FEBRUARY 14, 2023

From rebranding data governance in your organization to demonstrating real business impacts, there’s a lot you can do to bring everyone in your business on board. The role of monitoring, measuring, and metrics So, you’ve got the first step done; you’ve implemented data governance and everyone in your organization is on board.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Andrew White

JULY 5, 2023

One of the points of confusion is with catalogs – or data catalogs – or analytics catalogs or metrics stores. Here I repeat what I wrote in the original blog: Use cases for a data catalog Analytics use cases are quite different to governance use cases. The fact that there are different names is one thing.

Metrics 52

Metrics Metadata Modeling Data Quality 52

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing.

Data Warehouse 101

Data Warehouse Testing Data Quality Reporting 101

DataRobot Blog

MAY 10, 2022

The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. The first step would be to make sure that the data used at the beginning of the model development process is thoroughly vetted, so that it is appropriate for the use case at hand.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Alation

OCTOBER 5, 2021

These divergences of focus can lead to consumers feeling bogged down by overly complicated processes or leadership teams being unable to see initiative investments reap the desired rewards of their predictive business success metrics. (1). Incomplete data. Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation. The Cluster Activity page gathers useful data to monitor your cluster’s live and historical metrics.

Metrics 99

Metrics Metadata Snapshot Management 99

Alation

AUGUST 17, 2022

Data governance policy should be owned by the top of the organization so data governance is given appropriate attention — including defining what’s a potential risk and what is poor data quality.” It comes down to the question: What is the value of your data? Risk, however, is a different challenge.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

CIO Business Intelligence

MARCH 24, 2023

Overcoming data challenges Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. “ESG ESG data quality is the biggest challenge. revenue growth from businesses showing a lower commitment to ESG.

Risk Management 52

Risk Management Consulting Metrics Data Quality 52

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Metadata 52

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 72

Data Quality Data Lake Data-driven Metrics 72

erwin

MARCH 8, 2019

A number of best practices and technology solutions were used to establish the data required for managing the registration and classification of data feeds: The underlying metadata is harvested followed by an initial quality check. This, among other safeguards, ensures data quality.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

Alation

MAY 17, 2022

Beyond sampling, analysts must take care to validate data in other ways. Many data catalogs provide data quality information, either natively or through partnership with a dedicated data quality tool. Because analysts work intimately with the data, they often have unique insights into it.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

AWS Big Data

MARCH 7, 2023

ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. Unlike ingestion processes, data can be transformed as per business rules before loading. You can apply technical or business data quality rules and load raw data as well.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

O'Reilly on Data

DECEMBER 12, 2019

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8].

Machine Learning 192

Machine Learning Modeling Testing Risk Management 192

Occam's Razor

AUGUST 22, 2011

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. "Engagement" Is Not A Metric, It's An Excuse. How to focus?"

KPI 124

KPI Metrics Measurement ROI 124

Jet Global

MAY 1, 2020

They are going to have different ways of combining numbers into metrics. We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Data quality issues. Here’s the ugly truth: Everybody has a data quality problem. Learn how to prepare your data for BI.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

DataRobot Blog

MARCH 10, 2022

DataRobot will automatically perform a data quality assessment, determine the problem domain to solve for whether that be binary classification, regression, etc., and recommend the best optimization metric to use. In DataRobot’s GUI, all a user has to do is define what variable they would like to predict and click start.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

CIO Business Intelligence

JANUARY 23, 2024

For example, McKinsey suggests five metrics for digital CEOs , including the financial return on digital investments, the percentage of leaders’ incentives linked to digital, and the percentage of the annual tech budget spent on bold digital initiatives. As a result, outcome-based metrics should be your guide.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

Jet Global

MARCH 4, 2020

A manufacturing Key Performance Indicator (KPI) or metric is a well defined and quantifiable measure that the manufacturing industry uses to gauge its performance over time. The only way to stay ahead in this fiercely competitive industry is through the implementation of manufacturing KPIs and metrics. What Is A Manufacturing KPI?

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

AWS Big Data

NOVEMBER 16, 2023

Redshift provisioned clusters also support query monitoring rules to define metrics-based performance boundaries for workload management queues and the action that should be taken when a query goes beyond those boundaries. A predicate consists of a metric, a comparison condition (=, ), and a value.

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

O'Reilly on Data

OCTOBER 13, 2020

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

Management 246

Management Metrics Machine Learning Modeling 246

datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Another crucial factor to consider is the possibility to utilize real-time data. Enhanced data quality. It doesn’t stop here. click to enlarge**.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Modern data catalogs also facilitate data quality checks.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CIO Business Intelligence

FEBRUARY 20, 2023

A candidate who earns the certification will have proved their ability to build bundle configurations, pricing, output documents, and renewals and amendments. This Salesforce Service Cloud Consultant certification recognizes individuals who design solutions for contact centers, as well as analytics solutions for metric tracking.

Consulting 87

Consulting B2B Cost-Benefit Sales 87

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. But what if you could combine that information with usage metrics?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

IBM Big Data Hub

SEPTEMBER 11, 2023

Using data, user research and human-centered design to effectively address these considerations can help you develop a clear modernization strategy that objectively drives your priorities, backlogs and roadmaps. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 91

Data-driven IT Measurement Cost-Benefit 91

InsightOut

MAY 20, 2022

In listening to them describe their experience – what went well and not so well – and reviewing their existing approach and documentation, I have observed a number of patterns. With these projects, there are clear technical challenges that can also lead to problems, such as data quality and accessibility.

Analytics 52

Analytics Dashboards Optimization Technology 52

datapine

FEBRUARY 17, 2023

That said, data and analytics are only valuable if you know how to use them to your advantage. Poor-quality data or the mishandling of data can leave businesses at risk of monumental failure. In fact, poor data quality management currently costs businesses a combined total of $9.7 million per year.

Analytics 191

Analytics Cost-Benefit Dashboards Business Intelligence 191

DataRobot Blog

DECEMBER 15, 2022

If your dataset is not in time order (time consistency is required for accurate Time Series projects), DataRobot can fix those gaps using the DataRobot Data Prep tool , a no-code tool that will get your data ready for Time Series forecasting. Prepare your data for Time Series Forecasting. Generate Model Compliance Documentation.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

IBM Big Data Hub

OCTOBER 12, 2023

Documentation can also be generated and maintained with information such as a model’s data origins, training methods and behaviors. Checkpoints can be created throughout the AI lifecycle to prevent or mitigate bias and drift.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Alation

MARCH 21, 2023

By building a governance framework to address data usage and quality issues, Virgin Australia was able to standardize definitions to facilitate data discovery and build trust. Finnair Finland’s national airline, Finnair , wanted to break down data silos to standardize metrics and support better communication across teams.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Alation

SEPTEMBER 23, 2021

Behavioral intelligence, embedded in the catalog, learns from user behavior to enforce best practices through features like data quality flags, which help folks stay compliant as they use data. Active Governance – Active data governance creates usage-based assignments, which prioritize and delegate curation duties.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52