We know that data is the driving force behind any business in today’s society. With that being said, it is not only desirable, but also required, to store that data in a safe location, whether physical or online. Data is your best asset and because of this, it needs to be kept where it is protected from illegal access.
Unfortunately, with the advancement of data warehousing, it has been noticed that the methods to breach security are also becoming more smart.
Needless to say, a security breach of any magnitude might have disastrous implications, ranging from the exposure of sensitive and confidential corporate data to the compromise of a client database.
As a result, data warehouse security measures are essential and should be tightly implemented at all levels to preserve data integrity.
Luckily for us, there are well-known and tried best practices that can be used to prevent data theft which we will cover in this post.
What is Data Warehouse Security?
Data warehouses collect information from a variety of sources, and they have a lot of moving pieces. When data is moved from one location to another, security risks occur.
Data warehouse security means taking the appropriate precautions to ensure that only authorized individuals have access to the information.
Security in the Data Warehouse should include the following:
- Ensuring strict User access controls so that employees only have access to the data they need to conduct their tasks.
- Taking precautions to safeguard networks where data is stored.
- Moving data with care and consideration for the security implications of any data migration process.
Security Challenges for a Data Warehouse
Perhaps the most significant impediment to establishing security measures is the scope and size of a data warehouse. Several personnel from various hemispheres of the globe would normally use a huge data warehouse for analytics, business intelligence operations, data mining, and other purposes.
The problem is to strike a balance between providing easily available data to employees while protecting data security and integrity. Further classification of users, as well as the level of access they have to data, is a difficult road to navigate.
Finally, the security measures themselves can become oppressive at times, compromising the data warehouse’s overall performance. The solution to all of these problems is to adopt custom-made security measures that are tightly matched with the organization’s structure.
Best Practices for Data Warehouse Security
Before we get into the specifics of the best practices, we need to further separate them into physical and online components. Both of these features work together to make the data warehouse impregnable and secure against intruders.
Physical Security Practices
- Implementing physical barriers to your data warehouse: Biometric readers, anti-tailgating systems, and other physical access control technologies have made restricting and regulating physical access to data warehouses much easier. These may appear to be exorbitant and an unnecessary cost, but they are critical in guaranteeing the integrity and security of the company’s valuable data.
- Communicating rules, procedures and policies about your data warehouse security: One of the keys to success is communicating effectively about security standards and ensuring that all people in the vicinity of the data warehouse strictly follow and obey these guidelines. It’s possible that intruders could utilize an employee to obtain access, but if the employee in question is strictly adhering to the requirements, it makes all the difference.
- Keep it low-key: For obvious reasons, the data warehouse’s structural information should likewise be kept a closely guarded secret.
Software-Based Security Measures
One of the most important defences against data theft is data encryption. Whether in the transactional database or the data warehouse, all data should be protected using techniques like AES (advanced encryption standard) or FIPS 140-2 certified software. Some proponents say that data encryption has a negative impact on data centre performance and data access speed, but it is preferable to the alternative.
The data housed in the data warehouse should always be adequately classified in a good data warehouse security strategy. Implementing security measures for data with low sensitivity, such as data subject to exposure due to business policies, is of limited utility.
As a result, a strong warehouse security plan categorizes data and specifies the data’s confidentiality, integrity, and availability criteria.
Data Partitioning and Segmenting
Although data encryption is an additional security measure, it might be inconvenient if used without segmenting and partitioning. Classifying or separating data into sensitive and non-sensitive information is what segmenting and partitioning entails.
After partitioning, the data should be appropriately encrypted and stored in separate tables, ready to be consumed. Semantic Scholar conducted an excellent study on this topic, which is well worth reading.
Securing Data in Transit
Securing data in transit is quite different that securing static data. The term “data in transit” refers to data that is being relayed in real time from transactional databases to the data warehouse.
Because transactional databases can be located anywhere in the world, employing secure protocols like SSL or TSL is strongly recommended. Cloud-based data warehouses, which should be used, provide a safe and impenetrable conduit between the database and the cloud storage.
Establish Audit Requirements
Consistent and regular audits of your data warehouse can aid in the detection of vulnerabilities and the prevention of a breach. Connections, disconnections, data access, and data change are all things to think about. Audit both triumphs and failures; in fact, failure auditing is essential since it identifies illegal or fraudulent access, allowing them to be avoided in the future.
Trusted Witness Server
As previously stated, today’s hackers and intruders are as adept and sophisticated as the security systems they face. Putting in place a trustworthy witness server is analogous to employing a watchdog who maintains a close eye on your data access points.
It can detect unauthorized and questionable data access attempts and send out an alert right away. This enables the individuals in charge of data warehouse security to stop attackers in their tracks.
Future Data Sources
Don’t forget to plan ahead when building your data warehouse. Consider future data sources, as well as the security and audit limits that they will necessitate.
Data warehouses are centralized data repositories that collect data from a variety of sources within an organization. As a result, to secure data, effective companies must establish effective security procedures.
Securing a data warehouse entails implementing data security techniques such as intelligent user access management, data categorization, highly secure encryption methods such as FIPS 140-2, and safeguarding all moving data. The risks are too high to let your data security strategy be an afterthought. So make sure when building a data warehouse that the entire process starts and ends with an effective data warehouse security strategy.
Interested in more? Check out our product, Vantage Point. Vantage Point (VP) is a no-code, click & go business acceleration tool which enables data driven decisions across your business. It drives interactivity across all parts of your organization by communicating value (KPIs), autogenerating tasks with cutting-edge ML/AI technology and enabling users to combine VP’s ML/AI recommendations with their own analysis. You can finally track the exact ROI impact throughout your entire business with Vantage Point.
Sign up for a demo with the link below
Senior Technology Architect
Senior Technology Architect