Exploring data warehouses and data quality

Making sense of data in a data warehouse requires data integration

Data warehouses will only work properly when they contain quality data.

A data warehouse is a repository or storage area where all the data in one's company is kept in a single place. This includes data from different sources as well as both current and historical data, perhaps from a legacy platform. It can consist of data from the company itself, which if the company is a large one might well be spread over many departments, all of which may be using different formats and different platforms. Not to mention data from external sources, whether from other businesses or user generated cContent.

Why use a data warehouse?

Reasons for having a data warehouse include helping in the creation of first-class business intelligence, for both reporting and data analysis and ensuring standardisation, i.e. making sure that all the data your company have are in a single database in the same format. Thus all relevant employees can both access and understand them thanks to the simplicity of the data warehouse infrastructure.

Data Warehousing can also aid in the creation of a single customer view. This allows the data to be presented consistently on a single page for each customer, whether the aim is to market the company's products and services or to let employees to work more efficiently, ensuring that they are all literally "working from the same page".

A data warehouse that works properly is itself a sign of having data quality you can trust in. However, unless your company attends to any poor data quality issues, the data warehouse just will not function correctly. Fortunately, in 2017 the solution to this problem of the quality of your data has never been more straightforward. It is to use Spotless unique web-based API solution to ensure that your data have been properly cleaned of inaccuracies, dirty data and other corruptions, duplications and mismatches at the point of entry into your data warehouse. When you design your data warehouse, you can integrate Spotless into its point of entry, guaranteeing spotlessly clean data quality and ensuring data integrity every time!

Extract, transform, load

The process of getting data from your various data sets and other sources to merge into one seamless dataset in your data warehouse is known as extract, transform, load (ETL) and is used when updating parts of your platform, or transferring from a legacy to a new platform. The data is extracted from the various sources, transformed into consistent data quality before being loaded into the data warehouse.

Spotless can ensure the data validation from your previous datasets or databases which use different formats by using an ETL system to ensure that the data from the different data sets match and are duplication-free and cleaned in every way. This provides a smooth and easy progression from the initial data sets to the new data warehouse. A company only requires one data warehouse as this is where they store all the data, including legacy and historical data.

By validating the data from each of the original data sets, Spotless can ensure that the data remain consistent and that the new data now in the data warehouse perfectly matches the old data in their various datasets regarding functionality and doing what they are supposed to do. This both ensures that you have a fully functioning data warehouse as well as making the upgrading from one platform to another into a relatively painless process, allowing your employees to focus on other problems such as business values because they do not have to focus on the data itself or its quality.

The advantages of using a data warehouse

Why does your company need to use a data warehouse? The simple answer is for useful business intelligence, to be making the best possible decisions for the future of your business, based on reporting and data analysis. The complicated answer depends on the nature of your business and the nature of the data you have, including your dark data.

However, the disadvantages of not having a data warehouse are bound to be worrying for any business owner or executive. They include not knowing if your data quality is reliable and trustworthy, repetition of effort with its inherent waste of resources as two different departments do the same thing because they are unaware that another department is duplicating their effort. This wasted effort can then damage the reputation of your brand. Meanwhile, poor reporting can lead to your CEO and other high-level executives not having a full grasp of the intricacies of your company, as well as to failed sales and marketing campaigns.

At Spotless we recognise the importance of having data quality which will allow your business to shine and out-compete all its rivals. We recommend using a data warehouse for storage and to facilitate easy access to your data. In our opinion, you should build Spotless' data cleaning API into the build-phase of your data warehouse. We guarantee you won't regret doing so.

The best place to get started with the Spotless Data Quality API, while an introduction to the process of using our API is outlined here. You can also add a file, just scroll down to where it says Add Your Data File and press the browse button. You will need to sign-up first to do this using your email address, Facebook, Google or GitHub accounts. You can also view our videos on data cleaning an EPG file and data cleaning a genre column which explain how to use our API.

We are giving away 500Mb of free data cleaning to allow you to try our API and see how well it works for you. We guarantee that your data will be secure and not available to any 3rd parties during the time it is in our care. If we find problems with your data or for whatever reasons are unable to automatically clean your data to the high Spotless standard of ensuring data quality you can trust in, an automated flag will alert our team of data scientists. They will then review the issue manually and, if necessary, contact you through your log-in details to discuss the problem.

Here is a quick link to our FAQ. You can also check out our range of subscription packages and pricing. If you would like to contact us you can speak to one of our team by pressing on the white square icon with a smile within a blue circle, which you can find in the bottom right-hand corner of any of the web pages on our site.

If your data quality is an issue or you know that you have known sources of dirty data but your files are just too big, and the problems too numerous to be able to fix manually please do log in and try now