If you’re reading this article, you likely already know: data continues to become more substantial in size and meaning for corporate decision-making across an organization. Tracking, housing, and analyzing your company information is a large part of today’s business world. If you plan on generating insightful financial reports to assess where your company is succeeding and facing challenges, you have to take on the responsibility of how you would like to maintain, access, and manage your data. And you might feel confused and frustrated when navigating your software options for data storage. There are options, with various functionalities that will be more helpful to some companies than others, based on the specific analytical objectives you would like to accomplish. That’s where we comes in – this article will discuss your BI data store options for higher performance financial reporting.
Definitions first. You have two primary options: a data warehouse or an OLAP cube. A data warehouse is a database that houses your diverse data types for richer decision-making, usually managed on a separate server from a company’s operational database. This option is a stable interface of consolidated, structured, transactional data. On the other hand, OLAP stands for online analytical process and the term, cube, refers to a multi-dimensional set of data, so an OLAP cube is a staging platform for analysis of your data. Furthermore, an OLAP cube is a Business Intelligence (BI) data relied on for pulling information from an organized digital space for the purpose of analysis. A primary distinction for these two choices has to do with their IT requirements.
In the past, data warehouses were exclusively a development project, typically long and pricey to design and implement. Nowadays, data warehouses are coming to market as an affordable, fully built software offering – a technology you can configure and use to house multiple kinds of data. The best data warehouses are easily manageable by business end users. A more specialized option would describe OLAP cubes, regarding what it requires to maintain the software. Because they are not open SQL server based products like data warehouses, they typically entail management of the server by someone with OLAP experience and skills. In other words, this option requires certain personnel criteria to be met. While there are plenty of professionals in the business world with an OLAP-specific skill set, does your budget have room for this price tag? And cost should be a significant aspect to consider when figuring out how you want to access company data for financial reporting, but that’s not all you need to know.
Doing your research on how OLAP cubes and data warehouses can uniquely serve you and your company is going to benefit your financial reporting processes. Some might have more substantial data storage needs for analytics that the difference between OLAP cubes and data warehouses would help to decide on which financial reporting product to implement. For others, a BI store investment might be less pressing in their BI roadmap. Wherever you fall on this range, Martin & Associates wants to give you the advantage of knowing the differences between your two main BI data store options in regard to financial report writing.
To continue learning more about BI data store driven financial reporting, read the rest of this article here.