FineReport

APRIL 9, 2024

Moreover, BI platforms provide the means for organizations to harness their data assets effectively, leading to improved customer satisfaction through personalized services and targeted marketing initiatives. In addition to these advancements, another prominent trend in data analysis is the growing impact of data visualization.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

CIO Business Intelligence

APRIL 8, 2024

Working with partner Amazon Web Services (AWS), the NFL has developed Digital Athlete, a platform that uses computer vision and ML to predict which players are at the highest risk of injury based on plays and their body positions. The great thing about the app is it’s very visual and it also has a reasonable amount of customization.”

Analytics 118

Analytics Broadcasting Predictive Analytics Metrics 118

Jet Global

AUGUST 28, 2023

Following success with Power ON, insightsoftware takes strategic evolution, growth, and product enhancements to the next level with software to extend visual planning and write-back solution capabilities to Qlik users RALEIGH, N.C. – Learn more at insightsoftware.com.

Dashboards 75

Dashboards Visualization Finance Data Quality 75

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand. Data engineers are unable to make these business judgments.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Octopai

MAY 15, 2023

Data lineage helps identify redundant or inefficient data integration steps, allowing organizations to streamline their processes and reduce development, maintenance, and operational costs associated with ETL. Data quality costs: Poor data quality can result in significant costs for organizations.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data. Data Governance.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

CIO Business Intelligence

JUNE 9, 2023

A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Data management defined You may be wondering what data management means.

Strategy 116

Strategy Management Key Performance Indicator ROI 116

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. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Implement data privacy policies. Implement data quality by data type and source.

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

IBM Big Data Hub

JANUARY 25, 2024

Considering that IDC surveyed 37% of companies that manage spare parts inventory by using spreadsheets, email, shared folders or an uncertain approach, it becomes evident that this practice carries more risk than it might seem. Can you review historical data modules? Can you conduct what-if scenarios to visualize your options?

Optimization 81

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 81

CIO Business Intelligence

SEPTEMBER 20, 2023

The data can also help us enrich our commodity products. How are you populating your data lake? We’ve decided to take a practical approach, led by Kyle Benning, who runs our data function. To avoid that, we built our data platform business case by business case. What is the risk of this case-by-case approach?

Data Lake 135

Data Lake Data-driven Dashboards Risk 135

datapine

MAY 31, 2022

Traditional spreadsheets no longer serve their purpose, there is just too much data to store, manage and analyze. Be it in the form of online BI tools , or an online data visualization system, a company must address where and how to store its data. The next part of our cloud computing risks list involves costs.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

O'Reilly on Data

APRIL 19, 2021

The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%). Bad data yields bad results at scale.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

CIO Business Intelligence

JUNE 30, 2023

All of this renewed attention on data and AI, however, brings greater potential risks for those companies that have less advanced data strategies. As these trends continue to evolve, building your data strategy around the principles of openness and governance assures trust in the data.

Internet of Things 104

Internet of Things Strategy Data Strategy Risk 104

FineReport

MARCH 24, 2024

Additionally, they facilitate organizational risk assessments, provide consulting services to leadership, and mentor junior analysts. They analyze, interpret, and manipulate complex data, track key performance indicators, and present insights to management through reports and visualizations.

Statistics 52

Statistics Data mining Visualization Reporting 52

erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. To manage not only risk but also to grow and compete effectively requires the ability to deal with both planned and unplanned change.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

DataKitchen

FEBRUARY 21, 2023

are more efficient in prioritizing data delivery demands.” Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Errors have caused the company’s leaders to lose confidence in the data products their team produces.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

DataKitchen

NOVEMBER 18, 2022

An effective DataOps observability solution requires supporting infrastructure for the journeys to observe and report what’s happening across your data estate. Logs and storage for problem diagnosis and visualization of historical trends. Data and tool tests. Observability includes the following components. Alerting paths.

Testing 130

Testing Statistics Measurement Metrics 130

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. As such, you’re able to gain all the insights you need while avoiding having to overhaul your environment.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

erwin

MARCH 30, 2020

As a result, the data may be compromised, rendering faulty analyses and insights. To marry the epidemiological data to the population data it will require a tremendous amount of data intelligence about the: Source of the data; Currency of the data; Quality of the data; and.

Metadata 122

Metadata IT Data Governance Data Quality 122

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. That’s where model debugging comes in. Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

erwin

MAY 6, 2020

Consider these high-priority scenarios in which the demand for a sound data infrastructure to drive trusted insights is clear and compelling: Organizations contributing to managing the pandemic: (healthcare, government, pharma, etc.). Automate data management, data intelligence and data governance practices.

Cost-Benefit 94

Cost-Benefit Data Governance Uncertainty Data-driven 94

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

CIO Business Intelligence

APRIL 6, 2022

In this way, AIOps frees up decision makers to focus on larger business issues, as well as provides them with clear visual information. There are several factors that can reduce organizational efficiency: Infrastructure: Many IT environments have disparate systems in silos, making it difficult to accelerate the flow of data between systems.

Data mining 72

Data mining Deep Learning Insurance Digital Transformation 72

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 68

Data Quality Data Integration Metadata Cost-Benefit 68

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

erwin

JULY 22, 2020

The company needed to help its data scientists and engineers improve their knowledge of the data, find the best data for use at the best time, and put the data in the most appropriate business context. Becoming a data-driven enterprise means making decisions based on facts. As an example, E.ON Avoiding Hurdles.

Data-driven 136

Data-driven Data Governance Digital Transformation Enterprise 136

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). Inaccurate or inconsistent data can lead to erroneous conclusions and decisions.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Ontotext

JUNE 22, 2023

This will minimize the risk of investing resources in fundamentally wrong assumptions and will give researchers more confidence to choose top targets for validation. It can also be easily maintained and upgraded, which lowers the costs of adding new data and maintaining data updates.

Metrics 52

Metrics Statistics Visualization Metadata 52

IBM Big Data Hub

NOVEMBER 24, 2023

Overall, Generative AI helps de-risk modernization programs via ensuring adequate visibility to legacy applications as well as dependencies. Provide a visual representation of the mapping and matching score with BIAN Hierarchical navigation and filters for BIAN levels, API Category and matching score.

Cost-Benefit 100

Cost-Benefit Testing Data-driven Enterprise 100

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 71

Data Quality Data Lake Data-driven Metrics 71

datapine

MARCH 27, 2019

The ability to visualize real-time market changes. Unless you take the necessary precautions, you run the risk of having to deal with multiple non-common data entries that may make your stats, facts, figures, and metrics inconsistent. Visualize your data. 90% of the information transmitted to our brains is visual.

Management 129

Management Data-driven Dashboards Visualization 129

Smarten

DECEMBER 3, 2023

‘Giving your team the right tools and a simple way to manage the overwhelming flow of data is crucial to business success.’ Augmented analytics can help the business to improve revenue and to discover product and service opportunities and gain insight into issues to resolve problems before they create risk.

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

Ontotext

JULY 6, 2023

Let’s consider an example about risk and opportunity event detection. Case studies The risk and opportunity event detection use case discussed above combines all of Ontotext’s capabilities: storing and managing large amounts of data adding meaning to it (e.g.,, The solution brings many business benefits.

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52