The flow of information into today’s modern data-driven world is like the waters cascading down the mighty High Force waterfall. It comes in fast and from multiple sources, and it must be managed properly or there could be significant issues. This is why we must look at how certain Salesforce data cloud projects fail during the data integration process, and what you can do to ensure that your project is a success.

Common Reasons Data Integration Projects Fail

As a new data integration project begins to take shape, it is common for there to be a lot of excitement and buzz around it. After all, there has likely been a significant amount of time, money, and other resources put into it. Unfortunately, despite all of this, many Salesforce data cloud projects still fail for a variety of reasons. Among the most common include:

Poor Data Governance

The policies aren’t clear, the files are disorganized, and no one knows for certain what they are supposed to do with the information that they possess. These are all characteristics of poor data governance, and it is devastating for any data integration project. Additional characteristics of poor data governance include:

  • A Lack of Clear Ownership – If it isn’t clear who is ultimately responsible for a set of files, that is a problem. There should always be a clear chain of command when it comes to which individuals are ultimately responsible for each file.
  • Low Data Quality – What is the purpose of collecting mountains of data if that data is inaccurate, duplicated, or otherwise degraded in some manner? If this is the case, then the low-quality nature of the data itself makes it practically unusable.
  • A Disregard for Compliance Oversight – Certain types of data require extra layers of security and compliance over them. This is because they contain sensitive information that must be protected. A lack of compliance oversight is yet another sign that the data itself is not being managed properly.

These things all sound bad, and they are, but you might still wonder what the potential damage of poor data governance is. Here are some potential risks:

  • Greater Risk of Fines After Audits – One of the things that all organisations need to be concerned about is the potential for fines following an audit if they are not properly taking care of the data that they are entrusted with. Poor data governance means that it will be far harder to prove that the data has been properly handled when audited.
  • Loss of Trust – If data is not properly maintained, then it might leak out and end up in the wrong hands. Should that happen, there is likely to be an immediate loss of trust from your customers.
  • Poor Business Decisions – Leaders within the organization will make decisions based on the data that is available to them. If that data is incomplete, inaccurate, or otherwise poorly managed, then the decisions that they ultimately make are likely to be poor quality as well.

Lack of Buy-In From Stakeholders

How can you ever expect a data integration project to work when the people who will be most impacted by it are not fully committed to its success? If that is the case, then you are likely to see the project fail before it even has the chance to truly get started. The very people who you need to be excited and invested in the project don’t have their hearts in it, and that can lead to immediate issues.

Inadequate Data Mapping

The failure to define how one dataset can be integrated from the platform where it is held now to another platform is an example of inadequate data mapping, and it can happen frequently during the data integration process. A consistent failure to show how one piece of data can be easily transferred from its current data platform to another will ultimately cause the entire project to fall apart.  This is why one of the most important steps when creating a data integration project is to plan.

A few common data mapping mistakes to be mindful of include:

  • Mismatched Data Fields – It is always worthwhile to ensure that the data fields match up properly with one another. This is to say that you should manually check for mismatched data between fields in different systems. An example of this might be one dataset using the first name of individuals while another uses the last name of individuals within the same field. That won’t transfer well until the data is uniform.
  • Accounting for Different Data Types – There are all kinds of different data that an individual might handle, and noe should be careful to consider all of the different types of data that they might encounter. For example, dates, currencies, and other formats are going to be different from generic numbers and letters. Make sure you account for the special symbols and other hurdles that you might encounter while transferring this data.

Siloed Teams

When every department is separated out and working on their own set of tasks, they can sometimes lose the ability to collaborate with one another effectively. Not only that, but siloed teams can also lead to data inconsistencies that are extremely costly. One estimate suggests that data inconsistencies across siloed teams cost companies £9.575 million per year! That’s certainly something that you want to avoid.

These are just some of the reasons why Salesforce data cloud projects might fail. There are a lot of different trip wires that one might stumble over while trying to do this. Knowing a little more about what some of those common data integration challenges are can help you avoid them moving forward.

Tips for Success in Data Integration

You now know what some of the common data integration challenges are, but what are some tips that you can apply for success with your data integration projects?

1. Establish a Clear Roadmap

When you are set to travel to a new location in your automobile, the first thing that you likely do is enter the address that you intend to travel to in your favorite GPS app. This allows you to see the turn-by-turn navigational instructions that you need to arrive where you want to go. The same concept is useful when working on a data integration project for your organisation. You should attempt to:

  • Define Your Business Objectives – What specifically do you hope to accomplish by working on this data integration project and what does success with this project look like for you? Those are some questions that you should have answers for right from the start. Tie your goals to the specific business outcomes that you want to accomplish before you ever start the process.
  • Review Where Things Stand Now – Understanding where you are starting from so that you know where you need to go is another step to take before getting too far down the road on your data integration project. This will allow you to assess the progress that you have already made and how much more you need to do.
  • Prioritise Your Data – Create a list of data that you want to prioritise and that which isn’t as important to you. This is useful because you don’t want to find yourself spinning your wheels on databases that simply don’t mean as much. Once you know where the truly important data is, then you can begin work on those sets first.
  • Plan the implementation– In a Salesforce Data Cloud project, it’s 80% planning and 20% building. After understanding your current data and the sources that you are looking to integrate, it’s essential to plan the implementation before building. Create a mockup of what your mappings and relationships should look like, make sure that you captured everything you need to make the integration successful. Because in Data Cloud most decisions are one-way and irreversible and you don’t want to find yourself overspending credits to re-create the entire project.
  • Put the Integration into Motion and Train Employees – Finally, you will be ready to put your data integration plans into motion and train your employees on the new systems and what is expected of them.

A set of steps like this makes it much easier to see the progress you have already made and where you need to that you have already made and where you must go from here.

2. Bring in Skilled Experts and Technical Leaders

It is fair to say that data integration is difficult, and it requires a team of highly skilled individuals who know what they are doing and know how to get the results that you need. This is why you should bring in people with a technical background who have worked on projects like this before. They will know how to spot the potential flaws in any plan and know how to steer you clear of those dangers.

3. Work on Cross-Team Collaboration and Building a Spirit of Change

Not every team member will be fully on board with the concept of this data integration project. For some people, it is likely to feel like a change that they don’t want to engage with. After all, they know how to work with the systems that are already in place. However, it is your responsibility to change their minds on this and convince them that this new change is something that will ultimately benefit them and the work that they do.

Gather all of your teams together and show them how they can pull together towards a common goal. When everyone is working towards the same ends, it is a lot easier to get the results that you want.

How Stellaxius Helps Organisations Succeed

At Stellaxius, we want to see every organisation that we assist with a data integration project find success. That is why we work so hard to deliver results for our clients, and that is why we have the track record to back it up. You have options when choosing a data integration partner, but none can offer everything we offer at Stellaxius. Among the upsides of working with us include:

  • Expertise in Salesforce and MuleSoft Integration – Salesforce already controlled 20.7% of the CRM market prior to its acquisition of MuleSoft, and now that number has jumped to 33.8%. Needless to say, these two are dominant forces in the space, and you need to work with a partner who has experience working with integration projects on these platforms. At Stellaxius, we bring that experience to every project that we work on for you.
  • Proven Track Record of Delivering Integration Roadmaps and Enterprise Architecture – Any partner can swoop in and say that they will help you with data integration, but we have the track record to back up what we are saying. We have worked on plenty of these projects for our clients before, and we have found great success in doing so. Therefore, you can put your trust in us to get the job done right.
  • Advisory Services to Align Your Technology with Your Business Goals – At Stellaxius, we also offer strategic advisory services to help you line up the technology that you are using with your larger business goals. We understand that every business is different, and the goals that you have are going to be different as well. Thus, we will step in and review your entire situation before making recommendations about the next steps that we believe you should take.
  • Hands-On Guidance to Ensure Quality and Scalability – As time goes on and you need to scale up your databases even more, we will be there to help you. Our hands-on guidance can help steer you towards the results that you require from your databases throughout every stage of the process.

Stellaxius should be your partner for your next data integration project. We strongly encourage you to review your data as it exists right now and reach out and contact us today to get more information about how we can team up together to deliver even better results for you.

I see myself as a data-oriented professional with a strong passion for turning numbers into meaningful insights. My career has been centered on data analysis and statistics, with a focus on uncovering trends, enabling data-driven decisions, and applying analytical thinking to solve complex business challenges.