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

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 71

Data Quality Data Lake Data-driven Metrics 71

FineReport

MAY 31, 2023

There are also some other key challenges that will often be encountered during the process of creating financial dashboards: Data Integration : One of the primary challenges is integrating data from various sources. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Where did it come from? Where is it now? How has it changed since it was originally created or captured?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

erwin

FEBRUARY 19, 2021

It involves establishing policies and processes to ensure information can be integrated, accessed, shared, linked, analyzed and maintained across an organization. Is it sensitive or are there any risks associated with it? Metadata also helps your organization to: Discover data. Harvest data. Better data quality.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

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 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. This should also include creating a plan for data storage services. Because it is that important.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

IBM Big Data Hub

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. By recognizing data as a product, it creates greater incentive to properly manage data.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

JANUARY 27, 2022

Data analytics is a way to make sense of raw data. Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Jet Global

AUGUST 24, 2023

Reasons for Lingering On-Premises Many companies are willing to experiment with the cloud in other parts of their business, but they feel that they can’t put the quality, consistency, security, or availability of financial data in jeopardy. Thus, finance data remains on-premises.

Finance 52

Finance Reporting Data Integration Risk 52

Jet Global

SEPTEMBER 26, 2023

Data Cleansing Imperative: The same report revealed that organizations recognized the importance of data quality, with 71% expressing concerns about data quality issues. This underscores the need for robust data cleansing solutions.

Data Quality 52

Data Quality Reporting Management Software 52

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. ETL tools ensure that the data is loaded efficiently and accurately into the destination.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

OCTOBER 4, 2023

. • Finance teams may find it challenging to gain insights from disparate data sources, hindering their ability to identify trends, risks, and opportunities on time. Addressing these challenges often requires investing in data integration solutions or third-party data integration tools.

Finance 52

Finance Reporting Cost-Benefit Management 52

Jet Global

APRIL 14, 2022

Having accurate data is crucial to this process, but finance teams struggle to easily access and connect with data. Reduce the risk of human error. Improve data quality. Reducing the risk of using manual processes. Near real-time information is vital to: Save time. 30% Siloed.

Data Collection 52

Data Collection Management Finance Reporting 52