Your Data Journey

 

Do you want to create a data-driven enterprise? Well, there are some fundamental steps you need to take on your Data Journey in order to get there. Here is our guide on how to do it.

1. Landscape Analysis

Before you embark on any new project you need to know where you are and what you have now. A Landscape Analysis is an audit of all of your data stores to assess data quality, relationships, business rules and accessibility. From this, you can then accurately scope the work ahead. Whatever stage of the Data Journey you believe you are at, you should always start off with a Landscape Analysis.

2. Extract, Transform, Load (ETL)

ETL is the process of moving data around your organisation to ensure it’s accessible where and when it’s needed. It’s important to build an ETL framework that incorporates data quality rules and processes. Make sure you select the tool that’s right for you and your team and consider what training you might need around this.

3. Data Quality

An essential element throughout your Data Journey is data quality. Ignore it at your peril! define the rules that govern the data and embed them into the processes. We recommend creating a data governance board and data quality programme to manage this. Also, be prepared to deal with the exceptions that will almost definitely crop up.

4. Data Storage

You probably have more data sources now than ever before and you need to bring that together. You need to consider what type of data you have, where you need it and how often it needs to be accessed. This is often where a Modern Data Warehouse comes in.

5. Insight & Analysis

By this point in your Data Journey, you should have high-quality data in an accessible place. Time to use it! Now is the time to build performance dashboards using a Business Intelligence tool like Sisense. Using your BI tool, you can create models to reduce churn, identify revenue-generating trends, and target the right people in your audience for specific campaigns. Again, don’t forget to consider the skillsets needed to make the most of these tools at this point in your journey. Does your team need any additional training?

6. Campaign Orchestration

Want to build an automated welcome journey for a new customer? A stock re-order automation? Or a fault alert? Now you can. There are plenty of tools out there to help you automate and personalise your communications, across multiple channels. For example, Apteco’s PeopleStage is a great tool for creating sophisticated trigger-based customer journeys for a great user experience.

7. Real-Time

Now you’re ready for real-time data. Yes, you might need to change some processes and technologies that have been built, but the investment is less and the rewards can be greater. Consider your use cases and rebuild your processes, data sources, journeys to suit.

8. Machine Learning

Machine Learning is the process of understanding what has happened in the past and using this information to predict what will happen in the future, through the use of algorithms. It can help you spot trends in your data, such as buying patterns, so you can capitalise on opportunities as they arise. Using Machine Learning to its full extent does require specialist skills, but it could be well worth the investment.

9. Artificial Intelligence

The ultimate in automated analysis and response. This is deep learning to build human-like responses. If you have followed all the above points to establish the right processes, infrastructure, tools, and skillsets, you are now in a position to explore AI. As well as simply predicting what will happen, AI enables you to take action based on this knowledge. The possibilities for you are now very exciting!

Want to know more? Get in touch.

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