It’s a dark and foreboding place. As you attempt to navigate the landscape, your feet give way to a spongey substance. 

You’re in a data swamp. The vast digital space of information where data is pasted, misplaced, and haphazardly stored. Where it’s easy to get lost in, sucked down by chaotic data, confused information, and lack of logic. 

It wasn’t supposed to be this way. 

When used the right way, data is a powerful resource that can provide companies with valuable insights and help them make more informed business decisions. However, without proper management, data can quickly become overwhelming and difficult to navigate.  

With a lack of order, structure, and coherence, systems become warehouses of chaotic and confused data, where truth is elusive – the conditions that we know as a data swamp. 

Alternatively, a well-designed system for storing and analyzing data is known as a data lake. 

Let’s explore the difference between a data swamp and a data lake and the steps companies can take to ensure their data is working for them, rather than against them. 

What is a data swamp?

A data swamp is a situation in which a company has collected so much data that it becomes overwhelming and difficult to navigate. This can happen when data is collected and stored without a clear plan for how it will be used, or when the data is not properly cleaned, organized, and normalized. 

As a result, the data is often inconsistent and of low quality, making it difficult to extract meaningful insights. In a data swamp, data can deceive, and truth becomes elusive. 

What is a data lake?

A data lake, on the other hand, is a well-designed and managed system for storing and analyzing data. Data is collected and stored in a way that makes it easily accessible and understandable. This is achieved through the use of data governance processes. 

As a result, data is consistently formatted and keeps its quality. And through the use of data management tools, they make it easy to access and analyze the data. In a data lake, data is clean, and truth becomes clearer. 

So how can a company avoid falling into the data swamp and instead create a data lake? Follow these steps. 

Step one: develop a clear plan 

One of the most important steps is to have a clear plan for how the data will be used. This will help to ensure that the data is collected and stored in a way that is consistent and easily accessible.  

For example, if a company’s objective is to improve customer retention, it will need to collect data on customer behavior and preferences. This will allow the company to create more personalized marketing campaigns and improve the overall customer experience. 

Just as important is having data governance processes in place. This ensures that data is properly cleaned, organized, and normalized, which maintains the quality of data that can be easily analyzed. A good data governance strategy should also include the specific roles and responsibilities for data management. 

Data security and compliance also need to be well-planned out. This helps to ensure that organizations are fully compliant with all relevant data protection laws and that any sensitive information is protected. A data security and compliance plan will include elements such as encryption, monitoring, and access controls. 

Step two: invest in data management tools 

The second step is to invest in data management tools that better facilitate access to data and the ability to analyze it. Organizations that place a strong emphasis on data can see a boost of 5.3% to their average yearly revenue. 

What the tools are will depend on the type of data being collected and the business objectives it will support.  

For example, if a company wants to extract insights from large sets of structured data, it may need to invest in data warehousing and data mining software. If it wants to extract insights from unstructured data, it may need to invest in text mining and natural language processing tools. These may include data visualization tools, data warehousing, and data mining software. 

This means that it’s crucial that companies invest in the right infrastructure and hardware to store, process, and manage the ever-increasing amounts of data that they collect. 

Step three: establish an ongoing process 

Enterprises need to establish an ongoing process to analyze and interpret data. This helps to ensure that the data is being used to its full potential and that they can extract valuable insights to power the business forward. 

Remember that those unwanted conditions of a data swamp emerge from collecting so much data that it becomes overwhelming. So much so that you become consumed by the very information you seek to harness for good. 

To avoid sinking into a data swamp:  

1. Develop a clear plan for how the data will be used  
2. Have proper data governance processes in place  
3. Invest in data management tools and infrastructure  
4. Maintain ongoing processes to keep data clean and stay up to date

Making data work for you rather than against you is becoming increasingly difficult as organizations take on more and more of it.  

Is your enterprise stuck in the muck of a data swamp? Looking to drain it and nurture a data lake? Then get in touch with Argano.