Challenges of large amounts of data

Digitalisation is flooding large and medium-sized companies with large amounts of data.
In order to be able to use the data reasonable, the data must also be of high quality.

Correct data is a major competitive advantage,
but also a constant challenge.

Examples:

• non-uniform data formats
• data stored in different locations
• Duplicates
• incomplete data
• lack of data updates (one single point of truth)

Business departments love Excel

Business departments usually start with Excel to make data-driven decisions. Excel is used for almost everything:

• Starting with attendee management for business events,
• via customer data with contact information
• all the way to accounting.

There’s almost nothing the tool can’t do. If you use macros, you can also automate certain processes, which makes the application even more powerful. But Excel also has its disadvantages.

1. Excel tables are usually saved by one person as a document on the computer. What happens if the person responsible falls ill or leaves the company?
2. The larger the amount of data becomes, the more difficult it is to keep control over the correctness of the data. After all, the data can still be overwritten in any way.
3. Long loading times can be a problem for the user.
4. Collaboration between several users, e.g. in the context of process workflows, is hardly possible.
5. links to other files can no longer be traced.

Alternatives for a pure Excel application

Our experts will help you identify the correct, relevant data and then create a data concept that helps the entire company to be able to make the right decisions.

No matter what data source, format or type of data, Selbach Information Systems manages to orchestrate all requirements in order to provide a solid database for a wide variety of companies.

We work independently of the different software vendors. It is not the tool that solves the problem of data management, but a mutually well thought out concept. Often those requirements that can be solved with in-house systems. You save a lot of money if you do not buy a large software package to solve your specific problem/task.

Examples for good data management

• All customer data can be easily found and accessed now and in the future, by the creator or other project members.
• Time consuming searching of files or comparing different versions of files is avoided.
• Changes are traceable and the files cannot be accidentally deleted or overwritten.

Database consultants from Mettmann near Düsseldorf: What you can expect

Step 1:

Enable Digitalisation

• Data stocks are well organized
• Access rights are controlled
• Central data management (server or cloud)

Step 2:

Deployment of Digitalisation

• Automation of processes
• Interaction within the system, e.g. commenting functions
• Automated distribution of information, e.g. by email
• Use of workflow-based applications, e.g. planning solutions