Many data analysts, IT managers, software managers, and developers are facing increasing challenges in managing their data. The processes are often inefficient because a structured data architecture is lacking as a basis. Let’s go over five problems every company encounters when it comes to data management and what solutions are available.

 

Problem #1: Too Many Tools

Many different tools are often used to manage data, each covering a specific step in the process. Sound familiar? You’re not alone. Many companies manage their data this way.

It becomes problematic and highly inefficient. After a while, no one want’s to touch or change it for fear of creating chaos. Your programmers then have to create scripts, convert or prepare the data manually, so that the next tool can process the data.

 

This creates an inefficient and error-prone process, that causes weekly fires. If a tool receives an update, for example, Data Engineers then have to manually ensure that the scripts are still compatible with the update and adapted if necessary. Digging through lines of code to figure out what needs to change. This costs your employees time and ultimately your company a lot of money because the entire tool landscape has to be regularly maintained.

 

Problem #2: Hard to maintain data architecture

In many companies, data management is not based on a simple and stable data architecture. Most of the time, tools are used that do not meet all the requirements. Which will then have to be helped along by workarounds in order to manage the data. This is not only time-consuming but in the worst case can also lead to system failure and associated downtime, which is very costly. Surely you also know points that need action in your environment because your processes are inefficient.

 

The solution most responsible parties resort to is hiring a data architect to design an efficient data architecture. However, this often results in a complex structure that only the data architect himself understands. Your company then makes itself dependent on this person because only he or she is able to make changes to the architecture. This dependency is counterproductive. As an entrepreneur, it is necessary to function independently of employees and to be able to make decisions quickly. This speed can usually be lost between tangled data sets. 

 

Problem #3: Monopoly knowledge of individual employees

Important to know: It’s no secret that employees who design data architecture or develop or integrate data management tools can leave the company at any time. If only one employee in your company understands the tools or architecture, you face a big problem if he or she quits. Your other employees then have to painstakingly learn the tools and architecture so they can continue to maintain them.

Even if there is documentation for the architecture and support of the tool landscape, it costs your employees time to write or familiarize themselves with it. If changes are required or errors occur, it often takes longer to complete maintenance or implementation, which ultimately costs you a lot of money.

 

Problem #4: High costs for data management

If a company decides to implement an in-house solution, the effort involved is often underestimated. Often, junior developers are tasked with designing a suitable data architecture including the associated tool landscape in order to supposedly save costs.

The problem may sound familiar: Young developers often lack the experience and oversight needed to solve this challenging problem. The project is delayed and ends up costing you even more money because you have to remove more people from the project, buy new tools, or start the project from scratch.

 

Problem #5: Many different data sources

The complexity of data management grows with the number of data sources. If a lot of data in different formats has to be managed and processed, this often requires numerous different tools. Workarounds often have to be made and additional scripts programmed to ensure that the data is processed correctly.

If you then also outsource key data to the cloud of other companies, your data chaos is perfect. And not only that: you also lose control and protection over your data. You no longer have an overview of where which data is located. As a result, important data can get lost or can no longer be recovered.

 

Solution: Clever and scalable tool landscape

If you’re also struggling to get a handle on these problems, you’re not alone. Many companies have spent millions trying to solve the problems – usually with moderate success. The ideal outcome is one where managing your data is easier, self-serviced, and self-documenting. There is one company that can actually solve these problems efficiently and for only a fraction of that amount: Nom Nom Data.

No more developing software yourself

Nom Nom Data offers you a platform where you can use both free apps and apps by subscription. The foundation is the so-called NomNode, which serves as an app store and marketplace. Here, you simply select the apps you need for your individual data management. 

If you don’t find an app that meets your requirements, contact the development team and get a custom app developed within a short time that fits 100% into your data management process. If your requirements change or your business grows, select new apps or simply adapt the previous ones to your needs.

 

Expertise remains with you

When you use Nom Nom Data apps, you can be sure that your data management is always up and running. This way, there’s no risk of an employee quitting, causing you major problems, or the data octopus getting up to its mischief again.

You save high costs

Processing data from different sources will then be easy for you. You and your employees no longer have to make workarounds to prepare the data, and all the data remains in your company.

Using Nom Nom Data will speed up your data management processes. You no longer need to assign employees to develop in-house solutions and save yourself high costs in the long run.

 

If you’re struggling with your data projects or failing to understand why – Schedule your consulting call with Nom Nom Data.

Other Articles
nom nom data engineering
Outsourcing Data Engineering Efficiently!
Data Engineer working on Solutions to attrition for small data teams nom nom data
3 Data Engineering Solutions To Attrition For Small Teams!
dancefight and nom nom data
How Nom Nom Data helped Dancefight overcome obstacles to continue sharing joy and connection to the world