Modern businesses that implement data analysis are shown to have an edge over their competitors.
A 2019 study by McKinsey & Company showed that companies where employees consistently use data in decision-making are 1.5 times more likely to report >10% revenue growth in the past three years.”Catch them if you can: How leaders in data and analytics have pulled ahead. McKinsey, 2019.
Due to their size and infrastructure, small and medium-sized businesses (SMBs) have often found themselves unable to produce effective analytical insights with the data they hold and acquire.
A great way for SMBs to confront their data and analytics issues is by implementing data warehousing. Data warehousing is a well-established and mature approach used in data analytics – bringing robustness, consistency, governance and structure to an organisation’s core data sources.
Combining the two is a natural fit to accelerate your cloud maturity.
What is a Data Warehouse?
A data warehouse is a central repository of integrated data from across an organisation. Its purpose is to store and organise the data (current and historical) in a format that is fit for reporting and analytics, and in a clear business-focused data model that the end users can interpret.
A typical data warehouse project extracts data from multiple sources, cleans, corrects, and links the data so that inconsistencies and possible invalid values are flagged up. This data becomes standardised and conformed so that consistency of data quality can be achieved.
This consistency that a data warehouse brings is better suited for flexible, quick, and reliable analysis. This results in the data warehouse becoming the foundation of trusted data that will support organisation wide analytics and help you evolve into using more advanced analytic capabilities.
Why Use Data Warehouse Automation?
Automating data warehousing provides a fantastic opportunity for accelerating your organisation’s maturity, without the traditional, long-winded implementation project. Here are the reasons why you should consider data warehouse automation.
With automation in place, you can develop your data warehouse a lot faster than if you were doing it manually. In some cases, up to 79% reduction in elapsed time and 90% reduction in effort can be achieved.
As touched upon before, automation all but guarantees consistency of your output and this standardisation ensures smooth development.
Due to the speed gained by automation, your team’s output should also be greater than before.
Since most of the architecture, design and standards would be generated automatically, the teams working with a data warehouse automation tool can afford to be less experienced and still deliver a successful data warehouse solution.
Time and Cost Saving
The increased output and speed of development will lead to typically 80% timesaving overall, compared to alternative methods. This saved time and not having to outsource expertise should also result in cost savings.
Automation gives you the ability to make changes to your data warehouse model and data pipelines quickly, allowing you to adjust an existing data warehouse solution with ease. This is vital when a data warehouse is full of data and making even the smallest change is traditionally very time-consuming.
Data warehouse automation reduces the risk of failure due to the robust functionality and platform that should guarantee best practice at speed, platforms also build in best practice functionality enforcing standards are adhered to.
Using the Cloud for Data Warehouse Automation
In recent times data warehousing has been reinvented in the cloud and is now a capability that can be used effectively by SMBs.
I’ve listed a few of the many benefits of using the cloud to host your data warehouse:
Cloud platform providers supply resources on demand. With near unlimited scaling of storage and compute resources, you can turn these capabilities up as and when you need them. For data warehousing, this means having the right level of resources when you need to process and load data, but not having to pay for them when this has been completed.
Cloud providers ensure infrastructure and data safety with security techniques such as data encryption, built-in authentication, automated threat detection and many more. Using a cloud provider also ensures compliance with data regulations that are costly and prohibitive for most smaller organisations.
Cloud providers have unlimited processing power at their fingertips that can perform over multiple locations, anywhere in the world.
Some cloud platform providers offer pay-as-you-go prices based on storage and computing resources usage. This possibility of controllable pricing means you won’t get locked into a service for the long term.
Making use of a cloud platform such as Microsoft Azure would mean having access to other functions they offer, like Azure Machine Learning.
Investing in cloud data warehouse automation capability is undoubtedly the best recommended path for SMBs, who want and need to manage their data more effectively. Allowing you to deliver your data warehouse and achieve ROI quicker, automating your data and analytics on the cloud is a key step to becoming a modern, data-driven organisation.
By leveraging data and analytics cloud services, with data warehouse automation, you can improve the analytics maturity within your organisation at a fraction of the time and cost compared to other data management methods.
This article is part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here or contact us today.
Weelin is the creator of the TrueCue Platform, and Chief Product Officer, having worked in the data and analytics industry for the last 20 years. In that time, he has delivered numerous large and small-scale BI and data and analytics platforms across a variety of industries, including healthcare, finance, media and energy.