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About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel datawarehouse that offers simple operations and high performance. This compiled data is then imported into Aurora PostgreSQL Serverless for operationalreporting.
Finance teams are increasingly being asked for timely, recurring operationalreports to support day-to-day decision making. The most common challenges your finance team probably faces are: lengthy report creation time, existing tool complexity, and the inability to drill into transactional data. Download Now.
When extracting your financial and operationalreportingdata from a cloud ERP, your enterprise organization needs accurate, cost-efficient, user-friendly insights into that data. While real-time extraction is historically faster, your team needs the reliability of the replication process for your cloud data extraction.
That might be a sales performance dashboard for your Chief Revenue Officer, a snapshot of “days sales outstanding” (DSO) for the A/R collections team, or an item sales trend analysis for product management. CXO can automatically access information from group companies to produce consolidated financial reports.
Here are the burdens facing your team with on-premises ERP solutions: Too complex: ERP data models are complex and difficult to integrate with other ERPs, BI tools, and cloud datawarehouses. Changes made to a data model often require technical support including, but not limited to, a forced reboot of connected applications.
Interestingly, however, many project-based businesses like yours are not even close to achieving this level of reporting. A recent report by insightsoftware and Hanover Research highlights this issue, stating that 98% of operationalreporting professionals distribute reports as a static PDF.
Microsoft Excel offers flexibility, but it’s missing so many of the elements required to assemble data quickly and easily for powerful (and accurate) financial narratives. The reports created within static spreadsheets are based on a snapshot of reality, taken the moment the data was exported from ERP.
Microsoft Excel offers flexibility, but it’s missing so many of the elements required to assemble data quickly and easily for powerful (and accurate) financial narratives. The reports created within static spreadsheets are based on a snapshot of reality, taken the moment the data was exported from ERP.
Every time you do an export from your ERP system, you’re taking a snapshot of the data that only reflects a single moment in time. Any activity that occurs from that point forward is not reflected in the report.
Perhaps just as importantly, they lead to a time delay between the moment something happens in the business and the time it shows up on a report. All of that in-between work–the export, the consolidation, and the cleanup–means that analysts are stuck using a snapshot of the data. Manual Processes Are Prone to Errors.
That undermines confidence in the finance team’s ability to produce accurate reports, and it can ultimately lead to bad business decisions. There is yet another problem with manual processes: the resulting reports only reflect a snapshot in time.
The source data in this scenario represents a snapshot of the information in your ERP system. Researching that question requires substantial additional effort if your organization uses manual planning and budgeting processes. It’s not updated when someone records new transactions, and you can’t drill down to the details.
If you’re still reporting manually, it’s easy to run into disadvantages like these: Error-Prone Spreadsheets: Manual data entry and complex spreadsheet formulas increase the risk of human error, leading to inaccurate reporting and unreliable financial data.
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