Astera

AUGUST 22, 2024

For a successful merger, companies should make enterprise data management a core part of the due diligence phase. This provides a clear roadmap for addressing data quality issues, identifying integration challenges, and assessing the potential value of the target company’s data.

Data Quality 52

Data Quality Data Governance Government Monitoring 52

Domo

MAY 27, 2021

1 – There were significant quantified benefits over a 3-year period A composite organization, representative of the four interviewees’ organizations, experienced a three-year present value increase of more than $1 million in revenue as well as over $1 million in labor savings. That’s entirely eliminated.” million and an ROI of 345%.

Data Warehouse 93

Data Warehouse Financial Analysis Data Quality 93

Astera

MAY 13, 2024

This aggregation type is preferable to conduct trend or pattern analysis over time. Temporal aggregation is extensively utilized in time-series modeling, financial analysis, and economic forecasting. You can use it to identify seasonality or cyclical patterns in your data.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

APRIL 13, 2023

Data Warehouse Architecture A data warehouse relies on a three-tier architecture that includes: Bottom Tier (Storage Layer): This layer comprises the storage media, meta-repository, data marts, and database server Middle Tier (Compute Layer): The middle tier is the online analytical processing (OLAP) system.

Data Warehouse 52

Data Warehouse Data Mining Business Intelligence Business Intelligence 52

Astera

OCTOBER 29, 2024

Improved accuracy Advanced NLP techniques, such as NER, OCR, and text classification, enhance the precision of information extraction and the overall data quality. Suppose your organization needs to process a large number of invoices to extract key information for financial analysis and reporting.

Documentation 52

Documentation Healthcare Artificial Intelligence Financial Analysis 52

Astera

MAY 30, 2024

Statistical Analysis : Using statistics to interpret data and identify trends. Predictive Analytics : Employing models to forecast future trends based on historical data. Data Visualization : Presenting data visually to make the analysis understandable to stakeholders.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52