Big Data Security Risks Every Company Must Mitigate
Keleis Andre 2 months ago

There are 4 Big Data security risks that every company must deal with.

These days, big data is everywhere. Companies are collecting more data than ever before, which means there are more security risks than ever. Big data is important for giving your business a competitive edge in the market, but it can also ruin your business if you don't fix common flaws.

Big Data Security Risks Every Company Must Mitigate

These days, big data is everywhere. Companies are collecting more data than ever before, which means there are more security risks than ever. Big data is important for giving your business a competitive edge in the market, but it can also ruin your business if you don't fix common flaws.

These security holes come from how your organization stores and sends big data around. Here are four common weaknesses in big data and what you can do to make up for them.


Do the simple things right


Learning the basics of how to store and send large amounts of data goes a long way toward reducing risks. There are three things you need to look at. First, look at how information gets into your system. Are your data sources reliable, and are you using the right tools to get data in?


Next, how are you going to store those sets of data? Vulnerabilities in your data warehouse can bring down your systems, so make sure you're using the right tools. For example, Redshift is great for enterprise-scale BI integration, while Clickhouse is great for making requests with very low latency. Compare Clickhouse vs. Redshift and other options in this category to find the one that works best for you.



Lastly, check where your information is going. Who is looking at it, and can they change or edit the data parameters? Often, data vulnerabilities are caused by mistakes in how systems are set up to work together. For example, if there is a mistake in how two systems are set up, a bad actor could get into your data transmissions and change them.


By looking at these three basics of data handling and storage, you can find possible weaknesses. This exercise also forces you to look for weak points in the way your system is set up and configured. The result is a complete picture of your technical infrastructure that shows immediately where there are problems.


Data access


Who has access to your data, and do your permissions match the needs of your business? For example, most senior managers have automatic access to data that they can change. Unfortunately, many of these managers don't deal with data every day, so their user IDs are inactive.


Bad people use these IDs all the time to get into your systems. So, limit user access and check it often. Remove IDs that aren't being used, and look over the use cases for each ID. For example, it makes sense to give edit access to someone who works closely with data handling and analysis tasks. Giving someone this level of access based only on their seniority is a bad idea.

 


Tools for managing identity and access will make this job easier, especially if your organization is big. IDM tools will also show you which third-party service providers have been looking at your data. For example, cloud service providers can see your data, so you need to keep an eye on what they do.


Is someone using your data for analytics without your permission? In business, data is everything, so make sure you have the best visibility over who can access and handle data. This doesn't mean you shouldn't use third-party services. Instead, you should set up the right tools and processes for monitoring data so that you can see everything.

Safeguard your metadata

 

Many companies worry about protecting their data but ignore their metadata. A breach of your metadata can cost you a lot more because it has information about all of your systems and how your data flows. Metadata tells you where your data came from, what systems it interacted with, which users have access to it, and where it's going.


First, keep an eye out for changes to metadata, since this is usually a red flag. Metadata is usually not encrypted so that admins can get to it more easily. So make sure you keep an eye on changes and access. The best solution is to set up the right security and authentication processes.


If you limit access to sensitive systems as much as possible, you'll reduce the chance that metadata will get out. You might want to encrypt your metadata, but you should review your business processes to make sure that encryption won't cause more problems. For example, your ETL processes might have trouble dealing with metadata that is encrypted, which could lead to bigger problems.


So look at how encryption affects all of your processes and then move on.


Check the security of data querying tools


As BI and data analytics become easier for more people to use, more people are using NoSQL tools. From a business point of view, data democratization is great, but it makes security problems. NoSQL tools are fairly new, and they are always being updated.


Your security could be weakened if an update causes your systems to be set up wrong, which could happen if there are configuration errors. Make sure that admin authentication is required at every step to cover all security bases. After every update, you should go over the basics of data security.


Data access authorization, authentication, encryption, and auditing are some of these basics. Updates often conflict with application infrastructure, which leads to more security problems. Review them all carefully to make sure that your systems are always safe.


Data security is the most important


Businesses need strong ways to handle data and keep it safe. Keep your data safe at all costs and install the tools you need to get the job done.


Don't forget that even the best tools need strong processes to back them up. Check to see who has access to your data, how they get to it, and where it goes.

 

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