Posted by Guest Author on 11 December 2020
Many organizations use software applications such as ERP, CRM and Finance systems to run their business. These applications produce data that, if accessed, can provide valuable insight into business performance. But accessing data and reporting from often-complex systems, such as Microsoft Dynamics, Sage, Salesforce, SAP Business One and SYSPRO, can be difficult and time-consuming.
In some cases, so much so that it is not attempted at all. This blog explains how a data warehouse can make it easier to produce financial and operational reporting that is accurate and trusted.
A good data warehouse is where a company’s data is stored in a structure that lends itself for reporting. It’s different from the transactional data in the database of the business application it originated from, e.g. ERP or CRM, as a good data warehouse changes the structures data in a form specifically for reporting and analytics.
Leading data warehouse tools can perform what is known as Extract, Load and Transform (ELT), or Extract, Transform and Load processes (ELT) processes. These processes involve taking the transactional data from the applications’ database (extract), turning it in to a structure that is enhanced for reporting (transform) and saving it in a data warehouse (load).
The ELT or ETL process is also when a good data warehouse application will access and use the metadata from the underlying transactional data base. Metadata is data about data; it tells the person working with the data what the data is. Metadata makes it easier to find and understand data.
(You might also want to read "What are the 3 Main Differences between ELT and ETL?")
Attempting to analyze data directly from the transactional database can be difficult because it has not been transformed in to a structure and language, using metadata, that can be understood by the person doing the analysis. This usually means that the person preparing the data for reporting has a to have a deep understanding of the data in order to produce meaningful reports. Or, that they are technically competent enough to be able to perform ETL or ELT processes themselves using data technology such as Microsoft SQL or by moving BI and data to the cloud with tools such as the Microsoft Azure Data Services. Good data warehouse software removes this challenge or makes it considerably easier.
Many businesses have several data sources in their organization. While there may be one particular data source that is the largest and most important, such as an ERP or CRM, there are often other data sources in a business that it would be beneficial to include in reporting. These could be specific line-of-business applications or Excel, CSV or flat files created by users to agreed, company-specific formats for exchanging information.
(We recommend checking out "5 Reasons Why Excel Isn’t Enough For Financial Reporting")
A good data warehouse can utilise ELT or ETL processes to transform several different data sources, structured in different ways, in to a common data structure which allows them to be integrated in to one data set. The resulting unified data can then be used to produce reports from more than one data source. For example, you can produce Sales and Marketing analytics that use data from both ERP and CRM.
Business reporting from multiple, integrated data sources often provides a richer picture of the business. It ensures all data points relating to a particular entity e.g. a customer, or process e.g. customer invoicing, are included in the report so that there is no gaps and unanswered questions.
If you download data from a transactional database, or if you directly query a transactional database with a BI tool such as Power BI or Tableau, then you only get a snapshot view in time. This means it is impossible to see how the current view compares historically and how the trend has changed over time.
(You may be interested in "Business data reporting against historical sales data and historical ERP data")
A data warehouse stores historic data in a structure that allows for trend reporting. In essence it takes lots of snapshots of the transactional data bases and lays them on top of each other. Without this, businesses are stuck with only a current view, or are made to refer back to previous snap shots to uncover how the data has changed over time.
Self-service BI tools such as Power BI or Tableau become more valuable when they are used to provide reporting to the end users across a business, not just data experts using them in isolation. This is possible when a data warehouse is in place and is feeding data to the BI tool for users to read.
This is different from when a BI tool is being used for data discovery by an analytics expert. A data warehouse for business reporting can democratize a business’s data by structuring it for reporting and making it available via pre-built analytics for business reporting to all roles across all functions.
This means that normal business users who want to consume, or read, reports experience value from the investment in BI tools such as Power BI or Tableau, as well as the analytics experts that are using the tools for more complex data analysis requirements.
Moreover, the success, and ROI, of self-service BI in a business often hinges on one vital factor: data governance. Self-service BI tools such as Power BI and Tableau are tremendously productive if placed in the right hands. But if they’re not used correctly, these tools can result in pockets of data and knowledge across a business that may not be consistent.
Using a data warehouse as ‘a single version of the truth’ to control, or govern, the data that is being accessed by self-service BI users reduces the risk of inaccurate and inconsistent information being produced and consumed across the business.
(You might also like "Why Self-Service BI Needs Self-Service ERP and CRM Data Management")
ELT data warehouse automation software such as ZAP Data Hub makes it quicker and easier to produce business reporting. With a data warehouse, the manual tasks of finding and accessing data from individual systems and preparing it for analysis, usually in excel, are removed.
Data from all business systems can be refreshed in the data warehouse periodically and reports can be set to run on a schedule, or ad-hoc basis. This removes the time and effort businesses spend on creating reports. It also ensures that there is no human error and that the resulting reports are accurate and trusted.
In conclusion, an ELT Data Warehouse automation tool like ZAP Data Hub is a cost-effective way to improve business reporting
Hopefully these five reasons explain how a data warehouse can improve business reporting. To the non-technical, purchasing and implementing a data warehouse may sound complicated and daunting.
But it doesn’t have to be. Leading tools such as ZAP Data Hub are automated and optimized for the most commonly used business software, including Microsoft Dynamics, Sage, Salesforce, SAP Business One and Syspro.
This blog post was written and provided to us by a guest author.
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