Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 83

Insurance Risk Data-driven Finance 83

CIO Business Intelligence

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. Improved risk management: Another great benefit from implementing a strategy for BI is risk management.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Ontotext

JULY 6, 2023

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.,, Connected Inventory Ontotext’s Connected Inventory integrates data from various sources, which enables efficient reporting.

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Andrew White

JANUARY 11, 2021

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. The fill report is here: Leadership Vision for 2021: Data and Analytics. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

APRIL 29, 2022

Launching a data-first transformation means more than simply putting new hardware, software, and services into operation. True transformation can emerge only when an organization learns how to optimally acquire and act on data and use that data to architect new processes. Embrace data truths. The road ahead.

Digital Transformation 111

Digital Transformation Strategy Data-driven Data Strategy 111

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

AWS Big Data

AUGUST 14, 2023

R Domain Architect Responsible for the implementing screening, data product analysis, periodic evaluation, and optimal portfolio selection practices. Legal & Compliance C Legal & Compliance Officer Consults on permissibility of data products with reference to local regulation.

Management 79

Management Risk Measurement Optimization 79

O'Reilly on Data

JULY 15, 2019

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

erwin

FEBRUARY 4, 2021

However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. So what’s holding organizations back from fully using their data to make better, smarter business decisions? Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

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

DataRobot Blog

DECEMBER 20, 2022

In this context, an augmented intelligence approach around the data will be increasingly more critical for asset managers, investors, and real estate developers to ensure a better understanding of the real estate assets and take better decisions aimed at optimizing both the Net Asset Value and the Net Operating Income.

Management 59

Management Machine Learning Optimization Modeling 59