Is your Data Architecture ready for tomorrow’s data challenges?
I might stop short of advising you to ‘rip it up and start again’. But if your data architecture is preventing your business from achieving its full potential, that might be the best solution.
Ingesting and managing data was easy when everyone filled in the same form and posted it to you. Today, your traditional database management tools may be struggling to cope with structured data coming from a variety of sources — online and offline, your own and third-party platforms and apps, not to mention unstructured data, voice or video feeds.
Then there are decisions to be made around Cloud vs on-premise solutions, the need to be compliant, aligning your data strategy with your organisation’s wider business strategy, and not least privacy by design, which is not the act of wrapping your data environment with a firewall, but the actual implementation of data privacy through technology design. When you add up all these variables, getting your data architecture to meet all these needs begins to look like a tricky juggling act.
What should you be focusing on?
Over the past couple of years, data has been hitting the headlines for many of the wrong reasons. Of course, data security is important, but data architecture is concerned with what you do with data, not just keeping it safe. So, it’s about more than investing in some new infrastructure.
We see four distinct areas your data team should consider. These will help you discover what you really need and define how you can structure it.
You should know which database management systems (DBMS) are out there and which ones let you manage and manipulate data in the ways you want. Will it be cost-effective and scalable, up and down? The ways data flows in, through and out of your organisation should be clearly documented. Understanding the data journey will let you make better-informed decisions about technologies. You’ll also want to ensure it’s well-aligned with your other business objectives and considerations. For example, if lower upfront costs or reducing your carbon footprint are corporate goals, cloud storage might be the right solution.
Data input and management
The information that comes into your systems is used to create data, which is then manipulated, maintained and consumed. You need to understand where this data is originating, and how. It might come from a range of sources: your own or partner websites, an app, phone calls, paper applications or in-store sign-ups. If it’s coming from multiple sources, are you able to consolidate it effectively? Can you use the same tools to manage and manipulate it? You should have a master data management programme in place to guide you in managing consolidated data.
Enrichment and innovation
This part of the process deals with improving the quality of your data and making it applicable to the business functions where you intend to use it. A simple example: a customer signs up for your newsletter, then later buys a product from you. How do you pull that information together to build a fuller picture of that customer’s lifestyle, measure their behaviour against similar purchasers and create more relevant offers for them? It’s all about enriching the data you have by integrating new data sources in a consistent way across all channels.
Your data architecture solutions should be 100% driven by the needs of the business units that use your data. What outputs and formats will they need? How will they access and manipulate data for reports and campaigns?
Ultimately though, your thoughts and actions will be driven by the practical issues mentioned earlier: how will you ingest data accurately from a variety of sources, what tools are out there to help you manage it effectively, and what are the security and storage issues you need to consider?
You’ll have your own processes to help you achieve the answers and results you want, and most likely your own unique challenges as well. But it is worth the effort. As data becomes an increasingly essential tool for business development, having the right data architecture in place will become a competitive advantage.