Last time on the blog, we looked at the challenges working with big data can present to organisations. Today, we’ll delve a little deeper, and uncover some of the solutions that may help you to build an effective big data strategy.
Part 1 on Monday’s blog suggested that the problems encountered when using large data sets come from a lack of structured processes to collect, manage, and analyse that data. In response to these issues, you’ll need to formulate a data strategy that has a clear roadmap. The strategy will need to outline who handles the data, where the data originates, where it goes and its journey within your systems.
If there is a solid structure in place, you’ll be able to take actionable insights from your data. You’ll succeed in creating positive practices that will accelerate your business and drive it forward. Part 2 of our mini-series blog will address how you can work on creating a successful big data strategy.
How to create a big data strategy.
Audit your current data management practices.
To know what needs fixing, you need to know what’s broken. Logically, your first step must be to audit your current data management processes.
An effective big data strategy begins at the data collection stage, so it’s important to assess whether the data entering your system is accurate, valid, and secure. For example, make sure you are only collecting data that is true. Email addresses need to be in the correct format and telephone numbers must have the correct number of digits.
As part of this audit, you may like to look at all the apps in your software stack that collect data. Some of these may have been installed when your business was in its infancy, at a totally different stage, or when you had a different focus. As a result, they may not be a good fit for where you are now.
Additionally, check that no data is being entered by bots. To do this you can use security technology like reCAPTCHA, for instance.
You should also make sure that users are providing full consent for you to store and handle their data, as compliance with data protection and privacy laws is crucial.
Provide staff training.
Depending upon size and budget, it may not be possible for you to employ a team whose sole purpose is to manage and analyse data. If this is the case, you must make sure that your existing team has the skills to work with the data you hold.
You may need to provide opportunities for learning in data analytics, data management, and data security. It’s important to keep your whole team up to speed to reduce the occurrence of human error. Should they need to use tools and tech to do this, it’s your responsibility to equip them to do so.
Luckily, data analytics doesn’t have to be too complex. Tools such as Tableau make it easy for anyone to easily access, analyse, and make strategic decisions based on data.
Implement a sound data management strategy.
Your data audit should have highlighted any problems within your data management systems. Using this information, you should have a better idea about what is working for your organisation and where you are falling short.
The next step is to outline a new data management strategy. This big data solution should be scalable. It should fit where you are now, and the business you will be in the future. If it isn’t fit for the intended destination of the business, you will run into more data problems as you grow.
Part of an effective data management strategy is to clean up your current data. You’ll need to get rid of all outdated, inaccurate, and repeated data.
You’re then ready to move your plan to the next level, able to build the best tech stack to store and manage data. You will need a plan to introduce and communicate company-wide standards for data entry and maintenance. The data should be backed up and you must choose integration platforms to make sure your databases are all connected and talking to each other.
Integrate your databases.
One of the most influential things you can do to get the most from your big data is to integrate your databases. Without a strategy to do this, you’ll always end up with data silos and a lack of data connectivity.
Data integration is the most reliable way to achieve a roadmap of where and to whom the data is accessible. It also ensures that the data is flowing correctly between all your applications.
Successful businesses are all run with tools that are integrated in real-time, enabling an accurate, up to date and a 360-degree view of every aspect of the organisation.
If you are wondering how you can integrate your databases, here are a few ideas.
- Native Integrations.
Native integrations are built by the SaaS provider of the tools you’re currently using. You’ll need to determine if the native integration offered by your app suits your business’ particular integration needs.
- Custom Integrations
Custom integrations are built by an in-house team based on what you need. Although they are tailor-made, they’re expensive to build and require staff with specialised knowledge.
- An Integration Platform as a Service tool (IPaaS).
IPaaS solutions are offered by third-party vendors and provide integrations between hundreds of business apps. Your one subscription can build bridges between multiple apps and manage all your app connections in one place.
Many businesses choose IPaaS tools to integrate their software. They are cost-effective and provide the most comprehensive integration solution. Examples of these tools include Zapier, Tray.io, and Automate.io.
There are many benefits to having an integration tool including
- reducing the need for manual data entry
- unifying data formats
- reducing the chances of human error
- helps to ensure security and compliance with data protection laws
Big data has the potential to transform businesses, no matter their industry, specialism, or size. However, on occasion, the sheer volume of that data can create problems especially if you are dealing with systems that aren’t fit for purpose or those you have outgrown.
How you organise, manage, and analyse this data is the key to unlocking its potential. There needs to be a structured approach to data management; one that considers the data’s journey from the point it enters your business right through to how it’s used to influence key business decisions.
Are you looking to source a data team to propel your business forward?
We can help. Work with Ignite to build or scale your team. We hold a proven track record in tech and data talent solutions. We have consistently provided the talent that has helped businesses transform their data-driven insight capabilities.