We know we hype up multi-factor authentication, or MFA, quite a bit on this blog, and for good reason. When implemented correctly, it can be an effective deterrent for many cyberthreats out there. However, as they often do, hackers have found ways around MFA. Let’s take a look at how hackers find ways around MFA protection. Read More
- Published: 17 Jul 2019
The importance of effective data management cannot be overstated in today’s business environment. After all, the data you collect is of little use if you fail to leverage it properly, and successful data leverage starts with choosing where to house it. This week’s tip is dedicated to how and why to utilize a data warehouse for your organization’s needs.
Understanding Data Warehousing
A data warehouse is different from a data center in that it is a system for analyzing and reporting on large amounts of data, rather than a place where you might store your server infrastructure. Even better is the data warehouse’s ability to help predict trends and put together a full forecast for what’s going to happen to your business.
To truly understand the purpose of a data warehouse, you need to examine how warehouses work in the real world. In essence, a warehouse is meant to store things. It might seem like a simplistic way of describing it at first, but the important fact to remember here is that none of the other functions of a data warehouse can function without being able to store that data. If data is stored in a central location, it can be referenced against each other, meaning that the original source doesn’t necessarily matter as much. This data can be used to generate better analytics that isn’t limited by the amount of data you have access to.
Selecting Your Data Warehouse
Not all data warehouses are the same, and some different types offer different utilities. Therefore, the first question you must ask is if the data warehouse is sufficient for your specific needs. Here are some of the most important considerations you’ll need to think about for any data warehouse solution.
For this explanation, it will suffice to split data into two types: structured and unstructured.
- Structured data is data that can easily be organized into a spreadsheet. If your data fits the bill, a relational database would likely be a good fit for your needs.
- Unstructured data (or semi-structured data) is data that is presented in less-uniform formats, like geographical data, emails, books, and the like. If you have a lot of this kind of data, you may want to consider utilizing a data lake over a data warehouse.
How Immediate Does Your Data Need to Be?
The intended use of the data infrastructure will be necessary, especially if you’re looking to take advantage of business insights or data analytics. If you want to find out more information about your business, having this kind of data available will give you a clear picture of it. If your company wants to implement a predictive analytics platform, you might need less data, as tracking trends can be done with a Relational Database Management System (RDMS), and it might not benefit from access to all kinds of data that your organization stores.
How Are the Costs Structured?
Different data warehouse solutions will be priced according to various factors, including storage used, the size of the warehouse, the number of queries run, and the time spent leveraging the solution. The way you use the answer should be based on how cost-effective it is for you, whether it’s based on frequent data usage or the sheer amount of data you store.
Does It Work with the Tools You Use?
You need to be sure that the solution you’re implementing is compatible with your current solutions. Otherwise, you aren’t going to be able to take advantage of the full value that you could get from your data warehouse. You could even wind up doing more work for yourself unintentionally.
We recommend working with Compudata for any of your organization’s technology needs. To learn more, reach out to us at 1-855-405-8889.