CIO Business Intelligence

JUNE 7, 2022

It is frequently used for risk analysis. Factor analysis: Factor analysis is a statistical method for taking a massive data set and reducing it to a smaller, more manageable one. Data analytics and data science are closely related. Generally, the output of data analytics are reports and visualizations.

Data Analytics 131

Data Analytics Diagnostic Analytics Management Analytics 131

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). It is generally advisable to maintain a quick ratio above 100%.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

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

DataKitchen

JUNE 19, 2023

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. This pillar emphasizes the importance of implementing thorough data validation tests to mitigate the risks of erroneous analysis or decision-making based on faulty data.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

IBM Big Data Hub

JANUARY 15, 2024

Whether they use the public cloud, private cloud or multicloud environment, they are removing the onerous step of maintaining their own data centers. Trend: Cybersecurity By virtue of moving many services online, organizations are at greater risk of digital attacks.

Digital Transformation 79

Digital Transformation Internet of Things IoT Consulting 79

erwin

OCTOBER 8, 2020

No less daunting, your next step is to re-point or even re-platform your data movement processes. And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. Regulatory compliance is also a major driver of data governance (e.g.,

Data Governance 145

Data Governance Metadata Testing Data Lake 145

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Jet Global

JANUARY 9, 2020

They can make your business data pretty and easy to understand, no doubt. But what’s the business value of highly visualized data if it’s not accurate or if it doesn’t connect you to your actual business strategy? Such tools can provide slick visualizations to the hand of any C-level executive. Who doesn’t?)

Management 52

Management Analytics Visualization Dashboards 52

Smart Data Collective

SEPTEMBER 13, 2021

Implementing big data solutions can help investment managers navigate value investing safely. In this article, we will show you the use of the tools and the top reasons to hire Django developers to help you with big data integration. Main Types of Big Data. Investors can present their big data using visually rich tools.

Big Data 108

Big Data Forecasting Cost-Benefit Machine Learning 108

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. In short, yes.

Data Quality 69

Data Quality Data Integration Metadata Cost-Benefit 69

Smarten

APRIL 2, 2019

Smart Data Visualization allows users to view and analyze data to identify a problem and clarify a root cause and to interact easily with data discovery tools and analytics software to build a view that will tell a story using guided visualization and recommended data presentation so there is no need for assistance or delays.

Analytics 40

Analytics Predictive Modeling Visualization Cost-Benefit 40

Cloudera

JULY 18, 2018

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

Machine Learning 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Automate the data processing sequence.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Octopai

JUNE 26, 2020

Data governance is hugely important for enterprises needing to know their data inside and out. Data governance tools are available to help ensure availability, usability, consistency, data integrity and data security. The data journey governed.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

AWS Big Data

JUNE 28, 2023

Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

Analytics 68

Analytics Data Warehouse Data Lake Data-driven 68

FineReport

APRIL 26, 2023

Having visually appealing graphics can also increase user adoption. Advanced analytics capabilities : The tool should be able to analyze data and identify patterns, as well as forecast future events with complex forecasting algorithms, going beyond simple mathematical calculations.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Ontotext

MARCH 8, 2023

Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. A risk issue in one financial institution could result in a domino effect for many. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

FineReport

SEPTEMBER 5, 2021

In the manufacturing industry, small changes in data can bring indelible disasters to the company, so we need to monitor and manage these data in real time and automatically. The interactive control design can help you easily view the real-time dynamics of manufacturing through data visualization.

Manufacturing 52

Manufacturing Dashboards Optimization KPI 52

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. To learn more about data governance on AWS, see What is Data Governance?

Data Governance 96

Data Governance Unstructured Data Metadata Data Lake 96

CIO Business Intelligence

JUNE 7, 2022

A data scientist is a mix of a product analyst and a business analyst with a pinch of machine learning knowledge, says Mark Eltsefon, data scientist at TikTok. Because of this, only a small percentage of your AI team will work on data science efforts, he says. Data steward.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

IBM Big Data Hub

DECEMBER 16, 2022

It also serves as a governance tool to drive compliance with data privacy and industry regulations. In other words, a data catalog makes the use of data for insights generation far more efficient across the organization, while helping mitigate risks of regulatory violations.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

NOVEMBER 30, 2023

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner.

IT 97

IT Visualization Machine Learning Data Integration 97

Cloudera

FEBRUARY 15, 2024

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

Insurance 84

Insurance Data Architecture Risk Management Risk 84

Jet Global

DECEMBER 31, 2019

If there is no advantage to taking a risk—knowing that failure is a possibility—an individual will assume business as normal. The tools for delving deep into the data of the business, identifying patterns, and making predictions on trends are making a real impact. I believe that leaders must be supported in taking bold steps.

Digital Transformation 59

Digital Transformation Finance Experimentation Data-driven 59

erwin

MAY 2, 2022

However, it offers two extremely valuable business benefits: reducing data redundancy and improving data integrity. In short, it helps to keep the data effective, a highly desirable feature of any database. It’s not very hard at all once you know the definition and have some rather simple visual examples.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

DataKitchen

SEPTEMBER 21, 2023

This proactive approach to data quality guarantees that downstream analytics and business decisions are based on reliable, high-quality data, thereby mitigating the risks associated with poor data quality. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 97

Visualization Dashboards Data-driven Gap analysis 97

Jet Global

OCTOBER 7, 2020

It uses its own data mart, which cannot be customized in any way. Power BI is an analytical tool for data visualization and discovery. When working with D365 F&SCM data, it typically requires specialized programming skills to develop reports or to make changes to existing reports.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. Why do risk and opportunity events matter?

Data-driven 59

Data-driven Risk Modeling Risk Management 59

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. Don’t they all do the same thing? Is this the paradox of choice?

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

NOVEMBER 29, 2023

With Redshift, we are able to view risk counterparts and data in near real time— instead of on an hourly basis. Amazon Q Generative SQL capability Query Editor, an out-of-the-box web-based SQL experience in Amazon Redshift is a popular tool for data exploration, visual analysis, and data collaboration.

Data Warehouse 102

Data Warehouse Data Lake Analytics Machine Learning 102

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

DataKitchen

OCTOBER 25, 2022

When considering how organizations handle serious risk, you could look to NASA. The space agency created and still uses “mission control” where many screens share detailed data about all aspects of a space flight. Any data operation, regardless of size, complexity, or degree of risk, can benefit from DataOps Observability.

Testing 130

Testing Data-driven Visualization Dashboards 130