datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. If nothing can be changed, there is no point of analyzing data.

IT 317

IT Statistics KPI Data-driven 317

InsightOut

FEBRUARY 2, 2024

In the competitive world of e-commerce, data is not just a resource—it's a lifeline. From understanding customer behavior to optimizing supply chains, the right data can propel an online business to new heights. Let's explore how InsightOut is leading the way and revolutionizing the way e-commerce businesses leverage data.

Key Performance Indicator 40

Key Performance Indicator Metrics Dashboards Reporting 40

FineReport

APRIL 9, 2024

One of the key aspects of the role of BI platforms is their ability to streamline the process of data analysis and decision-making. They offer functionalities that allow for the integration and transformation of raw data into meaningful and actionable insights.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

CIO Business Intelligence

JUNE 14, 2023

Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications. The number of data analytics certs is expanding rapidly.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage. Cleaning up dirty data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

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). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. They should also provide optimal performance with low or no tuning.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

datapine

MARCH 27, 2019

Download right here your quick summary of the customers’ data world! Customer data is a state of constant flux, which is the number one reason to employ solid data monitoring principles. A bi-weekly scan of incomplete or erroneous records is essential to keep your database fully optimized and updated.

Management 129

Management Data-driven Dashboards Visualization 129

Alation

SEPTEMBER 7, 2021

Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. But governance is a time-consuming process (for users and data stewards alike). Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

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 78

Data Quality Data Lake Data-driven Metrics 78

Sisense

FEBRUARY 10, 2021

We do this throughout a variety of industries, and as the head of the electric grid ecosystem and product center at DNV, my focus is on helping optimize risk assessment, remediation, and overall reliability of critical assets at our electric utility customers. At DNV , our mission is to safeguard life, property, and the environment.

Dashboards 52

Dashboards Enterprise Risk Software 52

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

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. What is an HR Dashboard?

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

Occam's Razor

AUGUST 22, 2011

Key To Your Digital Success: Web Analytics Measurement Model. Be data driven?" " Measuring Incrementality: Controlled Experiments to the Rescue! Barriers To An Effective Web Measurement Strategy [+ Solutions!]. Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love!

KPI 124

KPI Metrics Measurement ROI 124

O'Reilly on Data

MARCH 31, 2020

Measurement, tracking, and logging is less of a priority in enterprise software. Consumer product management is typically more bottom-up, driven by large volumes of user feedback and usage tracking data. It turns out that type of data infrastructure is also the foundation needed for building AI products.

Management 327

Management Machine Learning Experimentation Metrics 327

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift delivers on that needed performance through a number of mechanisms such as caching, automated data model optimization, and automated query rewrites. With in-memory result set caching, queries that have a cached result set and no changes to the underlying data return immediately and typically within milliseconds.

Enterprise 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

DataKitchen

MAY 10, 2021

Data errors impact decision-making. When analytics and dashboards are inaccurate, business leaders may not be able to solve problems and pursue opportunities. Data errors infringe on work-life balance. Data errors also affect careers. You and your data team can accomplish the same thing at your organization.

Testing 214

Testing Manufacturing Data Quality Statistics 214

datapine

JANUARY 21, 2020

Since humans process visual information 60.000 times faster than text , the workflow can be significantly increased by utilizing smart intelligence in the form of interactive, and real-time visual data. Each information can be gathered into a single, live dashboard , that will ultimately secure a fast, clear, simple, and effective workflow.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

O'Reilly on Data

JULY 15, 2019

Regulators behind SR 11-7 also emphasize the importance of data—specifically data quality , relevance , and documentation. While models garner the most press coverage, the reality is that data remains the main bottleneck in most ML projects.

Machine Learning 37

Machine Learning Management Enterprise Risk Management 37

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Occam's Razor

NOVEMBER 13, 2009

No dragging of the feet, the book starts with a bang by laying out the framework that will be the center of every company that will leverage data (qualitative, quantitative, competitive) on the web. Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate. Chapter 5 The Key to Glory: Measuring Success.

Analytics 71

Analytics Metrics Measurement Testing 71

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Outline clear metrics to measure success. Data aggregation such as from hourly to daily or from daily to weekly time steps may also be required. Perform data quality checks and develop procedures for handling issues. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

Modeling 193

Modeling Machine Learning Testing Metrics 193

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. Manufacturing companies specifically use KPIs to monitor, analyze, and optimize operations, often comparing their efficiencies to those of competitors in the same sector.

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

Cloudera

SEPTEMBER 7, 2023

This puts the onus on institutions to implement robust data encryption standards, process sensitive data locally, automate auditing, and negotiate clear ownership clauses in their service agreements. But these measures alone may not be sufficient to protect proprietary information. Systematize governance.

Insurance 84

Insurance Risk Data-driven Finance 84

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. Apply predictive-analytic and ML techniques to this data to create more accurate profiles and proactively identify high-risk customers.

Data Architecture 87

Data Architecture Risk Management Risk Management 87

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. Mostly we react.

KPI 94

KPI Measurement Statistics Metrics 94

CIO Business Intelligence

NOVEMBER 29, 2022

Layering technology on the overall data architecture introduces more complexity. Today, data architecture challenges and integration complexity impact the speed of innovation, data quality, data security, data governance, and just about anything important around generating value from data.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111

Occam's Razor

DECEMBER 21, 2009

Really pick any report with any dimension you want to look at, we spend our time (and valuable space on our dashboards) looking at the top ten. We look at the top ten rows of data because: 1. Too much data from our web analytics tools. In the best case scenario you have even optimized landing pages. Referring URL's.

Metrics 94

Metrics KPI Reporting Visualization 94

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Alation

OCTOBER 28, 2021

It defines how data can be collected and used within an organization, and empowers data teams to: Maintain compliance, even as laws change. Uncover intelligence from data. Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. In other words, D&A plays a key role in the foundational measuring angle. Link to item 6 on slide 27 is broken, [link] , for Dashboard to measure business impact, can you provide a current link? That is the key.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff! Digital Marketing & Measurement Model. That's it.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Jedox

MARCH 7, 2023

The powerful in-memory engine supports agile planning such as splashing data on a granular level, as well as data aggregation across all hierarchies, at the push of a button. The finance team spent too much time manually exporting data from multiple systems, leading to version control problems and siloed data.

Forecasting 52

Forecasting Sales Finance Reporting 52

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smarten

SEPTEMBER 6, 2019

Self-Serve Data Preparation (SSDP) allows the organization, and its users, to gather, manipulate and analyze complex data from multiple sources in a single interface with easy-to-use tools. SSDP allows business users to leverage tools without the restrictions placed on managed dashboards or standardized reporting tools.

Analytics 51

Analytics IT Business Intelligence Testing 51