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. Operational optimization and forecasting. Cost optimization. Another important factor to consider is cost optimization. Enhanced data quality. It doesn’t stop here.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

DataKitchen

APRIL 26, 2021

At Workiva, they recognized that they are only as good as their data, so they centered their initial DataOps efforts around lowering errors. Hodges commented, “Our first focus was to up our game around data quality and lowering errors in production. Multiple Metrics for Success. At GSK, success is all about adoption.

Measurement 246

Measurement Metrics Data-driven Testing 246

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

AWS Big Data

AUGUST 14, 2023

Goals of DPPM The goals of DPPM can be summarized as follows: Protect value – DPPM protects the value of the organizational data strategy by developing, implementing, and enforcing frameworks to measure the contribution of data products to organizational goals in objective terms.

Management 79

Management Risk Measurement Optimization 79

Alation

OCTOBER 5, 2021

The main reasons that a company’s data strategy and governance protocols fail to deliver are somewhat universal, regardless of the industry sector. Without a doubt, no company can achieve lasting profitability and sustainable growth with a poorly constructed data governance methodology. Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

FineReport

MAY 25, 2023

An HR dashboard functions as an advanced analytics tool that utilizes interactive data visualizations to present crucial HR metrics. Its primary objective is to enhance the HR department’s recruitment processes, optimize workplace management, and improve overall employee performance.

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

DataRobot Blog

MAY 10, 2022

With this definition of model risk, how do we ensure the models we build are technically correct? 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. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. It’s not about data quality .

Testing 214

Testing Manufacturing Data Quality Statistics 214

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. Database design is often an important part of the business analyst role.

Statistics 97

Statistics Metrics Visualization Finance 97

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

datapine

FEBRUARY 22, 2022

In the article, he pointed to a pretty fascinating trend: “Experian has predicted that the CDO position will become a standard senior board-level role by 2020, bringing the conversation around data gathering, management, optimization, and security to the C-level.” We love that data is moving permanently into the C-Suite.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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

InsightOut

MAY 20, 2022

With these projects, there are clear technical challenges that can also lead to problems, such as data quality and accessibility. Optimization should come after, and all efforts should be focused on getting the first dashboard in the hands of the business users first. In this case, the solution still wasn’t in production.

Analytics 52

Analytics Dashboards Optimization Technology 52

Jet Global

JULY 2, 2019

With the Microsoft HDInsight platform, open-source frameworks such as Hadoop, Spark, Hive, LLAP, Kafka, Storm, HBase, Microsoft ML Server & more can be applied to your data lakes via preconfigured clusters optimized for different big data scenarios. Future-Proofing your Data.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. That means: All of these metrics are off.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Occam's Razor

APRIL 21, 2014

The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. We wonder why data people are not loved. :). I believe these two posts with a collection of some of my favorite metrics will inspire you: 1.

Marketing Analytics 131

Marketing Analytics Marketing Analytics Measurement 131

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). As a result, outcome-based metrics should be your guide.

Measurement 125

Measurement Digital Transformation KPI Metrics 125

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management 110

Management Machine Learning Experimentation Metrics 110

Jet Global

MAY 28, 2019

The decision will come down to a database vs a data warehouse—but let’s start by explaining what each is and why they are used. All About That (Data)Base. A database is, by definition, ‘any collection of data organized for storage, accessibility, and retrieval.’ Let’s look at why: Data Quality and Consistency.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Occam's Razor

SEPTEMBER 21, 2015

We send out our multi-tab spreadsheets, our best Google Analytics custom reports , our great dashboards full of data , and more to the tactical layer of data clients. The Directors, the Marketers, the Optimization employees and our resident social media gurus. Companies should optimize for the portfolio of visits (multiple!)

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Domino Data Lab

JULY 22, 2019

There’s a really nice comfortable blend here of what’s important in business, in engineering, in data science, etc. I definitely want to provide some shout-outs. In data science, definitely, there are other people who’ve talked more about that and we’ll point to them. You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

DECEMBER 4, 2023

The platform has been used to modernize and unify the information technology (IT) ecosystem of major financial firms, simplify human capital management (HCM) across brands’ subsidiaries, and optimize reporting processes in complex healthcare settings. Data quality: Ensure migrated data is clean, correct and current.

Testing 72

Testing Consulting Digital Transformation Cost-Benefit 72

Occam's Razor

JUNE 8, 2006

I am often asked what we look for when we hire Web Analysts or what quality do good Analysts possess or how to measure if a resource that already exists is optimal or how to mentor / motivate / guide our more junior Analysts to propel them to become great Analysts. We all agree that reporting is not analysis.

KPI 94

KPI Measurement Statistics Metrics 94

Andrew White

JANUARY 9, 2022

This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. Check this out: The Foundation of an Effective Data and Analytics Operating Model — Presentation Materials. Much as the analytics world shifted to augmented analytics, the same is happening in data management.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Domino Data Lab

FEBRUARY 4, 2019

mentioned above, data science emerged from a decidedly postmodern condition. For decision-makers (and company cultures) schooled in pre-1960 notions of modernity, that’ll most definitely freak out their #^@$! Overall, the situation creates a slow-moving train wreck, where data science is in the conductor’s seat. Taking a pulse.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. This is a key component of active data governance.

Metadata 52

Metadata IT Metrics Data-driven 52

Alation

JUNE 30, 2022

This knowledge, or metadata, is a crucial guide for newcomers to that data, granting them the context to use new data with confidence. Data quality can change with time. Data curation is a technique that helps document whether the data is the right data to be using. Data Quality.

Metadata 52

Metadata Data Warehouse Data Quality Data-driven 52

Alation

AUGUST 26, 2021

And types of metadata — or data about data — abound. Some high-level metadata categories in a data catalog include: Behavioral : Records who is using data, and how they are using it. Technical: Shows schema or table definitions. Business: Policies on how to handle different kinds of data appropriately.

Metadata 64

Metadata Data Governance Dashboards Software 64