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 insights are then provided to the team captain via a dashboard on Microsoft Surface devices.

Analytics 106

Analytics Broadcasting Predictive Analytics Metrics 106

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 125

Data Lake Data-driven Dashboards Risk 125

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

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. So, the only way for a data journey to truly observe what’s happening is to get his tools and pipelines to auto-report events. Data and tool tests.

Testing 130

Testing Statistics Measurement Metrics 130

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

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

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

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

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

DataKitchen

MARCH 16, 2023

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

FineReport

APRIL 26, 2023

” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Having visually appealing graphics can also increase user adoption. The tool is designed to be intuitive, so even users with limited technical expertise can create reports and dashboards quickly and easily.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. This includes database modeling, metrics definition, dashboard design , and creating and publishing executive reports. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

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 63

Data Quality Data Integration Metadata Cost-Benefit 63

Ontotext

MAY 2, 2024

Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources. This powers numerous applications, insight generations, dashboards, and tools. It also enables business teams to have their data at their fingertips and have a uniform view of it.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

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

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 76

Data Quality Data Lake Data-driven Metrics 76

FineReport

MAY 25, 2023

An HR dashboard functions as an advanced analytics tool that utilizes interactive data visualizations to present crucial HR metrics. Similar to various other business departments, human resources is gradually transforming into a data-centric function. What is an HR Dashboard?

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 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

Octopai

MAY 31, 2022

(We’ve had clients who started using our automated data lineage solution, and suddenly everyone in their organization was “trusting their data and believing in their data.”). The visibility provided by data lineage also enables you to streamline your data asset management by breaking down data silos and eliminating redundancies.

Management 52

Management Metadata Business Intelligence ROI 52

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

datapine

DECEMBER 17, 2019

The purpose is not to track every statistic possible, as you risk being drowned in data and losing focus. Using an IT analytics software is extremely useful in the matter: by gathering all your data in a single point-of-truth, you can easily analyze everything at once and create actionable IT dashboards.

Reporting 173

Reporting IT Key Performance Indicator Dashboards 173

Jet Global

MARCH 20, 2020

It’s no surprise that analytics and automation made the list, but readers may not expect to see data visualizations included among today’s most exciting and important innovations. With finance becoming ever more important, CFOs need data visualizations in their toolkit. Use the Best Data Available.

Visualization 59

Visualization Key Performance Indicator Finance Dashboards 59

datapine

APRIL 15, 2020

It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. Discover the available data sources. Data changes. Identify defects and enhancements.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

DataRobot Blog

JULY 21, 2022

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. Inquire whether there is sufficient data to support machine learning. Document assumptions and risks to develop a risk management strategy.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

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.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

DECEMBER 4, 2023

For organizations embarking on a digital transformation , it’s crucial to visualize how an ERP system will integrate with every aspect of a business’ operations. Clearly define the objective of the implementation project and determine its scope, timeline and budget as well as create a risk management plan.

Testing 73

Testing Consulting Digital Transformation Cost-Benefit 73

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Product/market fit is THE most important factor to get right.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

DataRobot Blog

DECEMBER 20, 2022

The use of artificial intelligence (AI) in the investment sector is proving to be a significant disruptor, catalyzing the connection between the different players and delivering a more vivid picture of the future risk and opportunities across all different market segments. You can understand the data and model’s behavior at any time.

Management 59

Management Machine Learning Optimization Modeling 59

Domino Data Lab

JUNE 23, 2019

If you have a user facing product, the data that you had when you prototype the model may be very different from what you actually have in production. This really rewards companies with an experimental culture where they can take intelligent risks and they’re comfortable with those uncertainties.

Management 110

Management Machine Learning Experimentation Metrics 110

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

MAY 17, 2021

Data discovery is a term used to describe the process for collecting data from various sources by detecting patterns and outliers with the help of guided advanced analytics and visual navigation of data, thus enabling consolidation of all business information. 3) Easily work with massive amounts of data.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Cloudera

APRIL 1, 2024

Guarantee Data Ecosystem Interoperability Many organizations struggle to unlock the full value of data due to disparate tools and data sources, and poor data quality. Organizations manage an increasing variety of single purpose databases, resulting in increased cost, complexity, management overhead, and risk.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

AUGUST 26, 2021

Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of Data Intelligence use cases include: Data governance. Cloud Data Migration. Privacy, Risk and Compliance. Let’s take a closer look at the role of DI in the use case of data governance.

Metadata 64

Metadata Data Governance Dashboards Software 64

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

NOVEMBER 14, 2023

Outdated Oracle data slams the brakes on your reporting teams’ efficiency. Poor data compromises your decision accuracy, resource allocation, responsiveness, customer satisfaction, and it leads to missed opportunities and compliance risks. Leaning too hard on IT: Oracle’s native tools are far from finance friendly.

Reporting 52

Reporting Finance Operational Reporting Dashboards 52