At a glance
- Three protection goals: confidentiality, integrity, and availability
- Protection of sensitive data against internal and external threats
- Technical and organizational measures interlock
- Basis for data privacy compliance (GDPR, BDSG) and IT governance
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Data security definition
The term data security refers to the comprehensive protection of data against unauthorized access, manipulation, loss, theft, or destruction. Data security is ensured through technical and organizational measures. The three central protection goals are:
- Confidentiality: Only authorized persons have access to the data.
- Integrity: Data remains correct and unchanged.
- Availability: Data is accessible at any time when needed.
Ultimately, data security is a state that companies strive for, in which personal as well as corporate data is fully secured against risks.
„With the role-based access rights in DeltaMaster, we ensure that sensitive controlling data is only accessible to authorized persons. This lets us use business intelligence without hesitation, even in sensitive areas.“Head of Controlling
Industrial company
Why is data security so important?
Data security is essential, especially in the age of digitalization, as companies process and store ever-growing volumes of sensitive data. The rise in cyber crime shows how important it is to protect data against threats such as theft, manipulation, and loss, in order to shield companies from costly damages and business interruptions.
In addition, legal frameworks such as the General Data Protection Regulation (GDPR) or the Federal Data Protection Act (BDSG) require companies to adhere to high data security standards, for example by protecting the data of their customers and users. Violations can not only lead to expensive legal consequences but also severely and lastingly damage the trust of customers and partners, and thus the company's reputation.
Given growing data volumes and complex IT infrastructures, a robust data security strategy is therefore crucial for long-term business success and the protection of sensitive information.
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What is the difference between data privacy and data security?
Data protection is not the same as data security, as the two approaches differ in their goals. In the comparison "data protection vs. data security," one can therefore observe that the concepts complement each other.
| Characteristic | Data protection | Data security |
|---|---|---|
| Focus | Protection of personal data | Protection of all data – personal and non-personal |
| Basis | Legal framework (GDPR, BDSG) | Technical and organizational measures |
| Goal | Safeguarding the privacy of data subjects | Confidentiality, integrity and availability of data |
| Examples | Consent requirements, rights to information | Encryption, firewalls, access controls |
- Data protection refers to the aforementioned legal framework for protecting personal data. It governs which data may be collected, processed and stored, and how, in order to safeguard the privacy of the data subjects.
- Data security concerns the technical and organizational protection of all data – regardless of whether it is personal or not. It encompasses measures that protect against unauthorized access, data loss or manipulation. These include encryption, firewalls and access controls.
- Data protection as the basis for data security: Without clear data protection policies, there is no framework within which data security measures can be meaningfully implemented.
- Data security as a prerequisite for data protection: Without sufficient data security measures, data protection cannot be fully ensured.
Data security and data protection are therefore equally important and work closely together to ensure comprehensive protection of data.
What data security measures are there?
To protect against the multitude of threats and attacks, both companies and private individuals should take comprehensive data security measures. Both technical and organizational measures serve data security. Some examples of data security measures that are implemented in practice are:
Technical measures
- Securing applications: Regular security updates and patches for software applications close known security gaps. In addition, security solutions such as antivirus programs protect systems against malware.
- Backup and recovery: Backup copies should be made regularly, and recovery procedures should be tested. In the event of data loss, you are then quickly operational again.
- Data encryption: Sensitive data should be secured both during storage and during transmission. This ensures that only authorized users have access to confidential information.
- Network protection: Networks can be protected with firewalls, intrusion detection systems (IDS) and encryption technologies in order to prevent unauthorized access and secure data transmissions.
Organizational measures
- Data protection policies: Comprehensive policies and procedures for handling data should be developed and communicated. These should contain clear instructions on the protection, use and retention of data.
- Employee training: Employees should be trained regularly in data security best practices and made aware of potential threats such as phishing attacks. A well-informed workforce is crucial for maintaining data security.
- Access management: Clear policies for access rights and principles such as the "least privilege principle" help to restrict access to sensitive data to necessary persons.
- Monitoring and audits: Regular security reviews are essential in order to identify and remedy weaknesses in processes. This allows security gaps to be detected and closed at an early stage.
The combination of different methods increases data security. While technical measures provide protection against external and internal threats, organizational measures ensure the correct handling and continuous improvement of security practices.
What does a company need for data security?
Successful data security arises from the interplay of technical and organizational prerequisites. The following points form the basis.
Application examples: where does data security play a role?
Data security is relevant in all business areas in which sensitive data is processed. The following examples show typical fields of application.
Where would you like to improve your data security?
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Data security and Bissantz
For Bissantz, data security is more than a technical prerequisite – it is an integral part of the product and company philosophy.
DeltaMaster relies on the highest security standards to protect sensitive corporate data against unauthorized access, loss, or manipulation. The security measures include:
- end-to-end data encryption for storage and transmission
- role-based access rights
- regular penetration tests and certifications according to recognized IT security standards
- secure operation, on-premises or in the cloud, according to the customer's requirements
Thanks to this security architecture, business intelligence with Bissantz can be used reliably and in compliance with data privacy even in particularly sensitive areas such as controlling, financial planning, or HR management. Bissantz also supports companies in designing suitable security and access concepts – so that data security is not only implemented technically but also anchored organizationally.
| Function | Benefit |
|---|---|
| Data encryption | protects sensitive data during storage and transmission |
| Role-based access rights | restrict data access to authorized people |
| Penetration tests and certifications | verify the security architecture against recognized standards |
| Operation on-premises or in the cloud | enables secure operation according to the customer's requirements |
| Consulting on security and access concepts | embeds data security organizationally as well |
„The end-to-end encryption and operation according to our requirements convinced us. Bissantz also supported us in designing a viable access concept.“Head of IT
Financial services provider
Frequently asked questions
What is data security explained simply?
Data security means: data is protected against unauthorized access, loss, and manipulation – while at the same time being available to the right people at any time. Like a well-secured vault system: only those who are authorized get in – and the contents remain unchanged and accessible.
What is the difference between data security and data privacy?
Data privacy governs the legal handling of personal data – who may collect, store, and process it. Data security describes the technical and organizational measures that protect all data – regardless of whether it is personal. Both interlock: data privacy sets the framework, data security implements it.
What are the three protection goals of data security
Confidentiality (only authorized persons have access), integrity (data remains correct and unchanged), and availability (data is accessible when needed). All three must be ensured simultaneously – the failure of one protection goal jeopardizes overall security.
What risks arise from inadequate data security?
The risks include: data loss due to cyberattacks or system failures, reputational damage from data breaches, legal consequences for GDPR violations, financial damage due to business interruptions, and loss of trust among customers and partners.
What is the least privilege principle?
The least privilege principle states that users and systems are granted only the access rights they actually need for their tasks – no more. It minimizes the risk that compromised accounts or unintended actions can cause major damage.
How does Bissantz ensure data security in DeltaMaster?
DeltaMaster relies, among other things, on data encryption, role-based access rights, and regular penetration tests – for both on-premises and cloud operation. In addition, Bissantz supports companies in designing security and access concepts, so that data security is firmly anchored both organizationally and technically.
Summary
Data security is a basic prerequisite for stable business processes, regulatory compliance, and the trust of customers and partners. It protects data through the interplay of technical and organizational measures – and thus creates the basis for reliable business intelligence and data-driven decisions. With DeltaMaster and its consulting expertise, Bissantz ensures that data security is not only implemented technically but anchored as an integral part of the entire BI architecture.