The ever increasing torrent of data being captured by companies and organisations presents new ongoing challenges in terms of how its gathered, stored and analysed: the decision as to how to set up data storage and analytics is an important one to get right.
Get it wrong – or at least work with a solution that’s not the best fit for your requirements – and the considerable benefits of working with the quality of business intelligence possible through effective use of data through storage and analysis could be compromised.
A data warehouse is not another tool in your toolbox, but rather a foundation for creating a data-driven culture in your organisation.
Lara Fox, Managing Director, Objective IT
The data storage and analysis challenge
You may have heard and be familiar with terms such as ‘data warehouse’ or ‘data lake,’ but what roles do they play in data use?
In a nutshell a data warehouse is designed to offer a repository to not only store data but enable meaningful analysis, so performing more than simply a data storage function.
The data warehouse incorporates some or all of these typical elements:
- A relational database to store and manage data
- A solution for extracting and transforming data so preparing it for analysis
- Data mining, reporting and statistical analysis capability
- Analytics tools to present data in easily digestible form – for example clear visuals
- Other applications to produce meaningful insights through using tech such as AI (Artificial intelligence) and machine learning-based algorithms
Data warehouse solutions: not just data storage
So, it is evident that ‘data warehouse’ isn’t simply data storage but could be more accurately described as ‘data warehouse solutions’. Data is centralised and consolidated from multiple sources and provides powerful analytical capabilities to allow your business or organisation to gain important and highly useful insights to improve long or short-term decision making and policy development.
Over time data warehouse solutions become even more valuable as a meaningful historical record is built up.
A ‘data lake’ by comparison is a more basic solution: here unfiltered and uncategorised data from various sources – for instance social media, apps and IoT (Internet of Things) devices – is more loosely stored for later use.
The format and structure of the various data sets contained in the ‘lake’ are determined at the time of analysis – which could be some time later – as opposed to being categorised straight away as is the case with the data warehouse.
Making the most of data warehouse solutions
While Big Data itself is relatively new in terms of the sharp increase in data capture from more and varied sources, data warehouse itself dates back to the 1980s although the scope of data being gathered, stored and analysed has developed considerably since.
For businesses and organisations a key decision is in how best to set up their data warehouse solutions or, if they have this facility already, how best to develop it and ensure its meeting their current needs and its suitability to handle future demands.
To this end consulting with data warehouse services professionals is a worthwhile move for your business to create a solution to make the most of their data relevant to specific needs. The architecture of a data warehouse they would create for you is based on your specific requirements – not a simple ‘cookie cut’ solution that everyone else uses.
There are various options in terms of commercially available systems to build your data warehouse on: you may have heard of labels such as ‘Azure data warehouse’ or ‘Azure SQL data warehouse’ – these refer to Microsoft’s data warehouse solutions packages.
Microsoft’s solution is a SQL data warehouse using, as its name suggests, the familiar SQL database language.
What is data warehouse?
Data warehouse is a data management system designed usually by an expert in data warehouse services provision to provide meaningful analytics through accurate storage and categorisation of data that can be analysed quickly and accurately. Over time data coming in from various sources builds a historical picture to enable the user to gain useful insights to inform policy and decision making.
For example, buying trends data pouring in from customers can inform what levels of product inventory are ordered and stocked. In production, information from sensors attached to machines can build a picture of how much down time has elapsed to help schedule workloads and much more.
What are the benefits of data warehouse?
Powerful data warehouse solutions developed for a business or organisation by an industry specialist in providing data warehouse services is a very powerful resource: the speed and accuracy in which data can be analysed means accurate and (if need be) quick decision making is possible across a raft of business and commercial areas including:
- Sales forecasting and fulfilment
- Production planning
- Potential and actual customer trends
Fast and powerful data warehouse systems such as those based on the Azure data warehouse platform mean it is possible to react quickly to trends and intelligence.
Is SQL a data warehouse?
SQL on its own isn’t specifically a data warehouse per se: SQL is a popular database language - similar to how HTML is a common website design language.
You can say “SQL data warehouse” to refer to data warehouse solutions based on this particular language, so you may come across a description such as ‘Azure SQL data warehouse’ which, as mentioned previously, is Microsoft’s offering that happens to be based on the common database SQL language.
Talking to an experienced data warehouse services provider, like Objective IT, would clarify the platform best suited to your requirements possibly based on Microsoft’s Azure SQL data warehouse.