Data Operations: Why data silos impact your cyber security

by Riversafe

The information age has been a gift for data-driven businesses – but it’s also been a catalyst for increased cybercrime activity. As big data becomes more prevalent and companies hold more customer details, their data becomes harder to manage and security weaknesses like data silos become a more imminent risk. Data Operations aims to address these challenges.

In the face of these threats, the need for enterprises to strengthen their cyber security protocols is unavoidable. Today, all businesses need to understand the risk and challenges associated with big data, just as much as the benefits. Only then can they implement effective data operations strategies that will keep their online databases and customer data secure against cyber attacks.

How do big and small businesses benefit from big data and data operations?

The increasing number of connected devices and applications has given companies huge amounts of consumer data to work with. This ranges from simple details, such as date of birth, to more specific trends like online shopping habits.

One of the main ways both small and large businesses use this data is to inform their business, marketing and product strategies. With more information about the consumers they want to sell to, companies no longer have to guess what people want. They can target their desired audience more effectively – building stronger relationships, improving products based on customer feedback, and ultimately becoming more relevant and in-demand.

However, it takes a lot of groundwork to truly achieve these benefits. Implementing a data operations strategy, which includes procedures for how to track, organise, prioritise, secure and evaluate big data, will help you make better and more relevant business insights.

What are the biggest challenges with business intelligence?

Business intelligence can be a dream come true for businesses – but without an appropriate data ops strategy to help you manage the process, collecting big data can have significant drawbacks.

Volume and Size of Data

The sheer volume of big data can be intimidating. Finding actionable business intelligence in the midst of hundreds of customer details is therefore near impossible without an informed approach and clear objectives in place.

Data Silos

Data silos are a common result of unstructured or disorganised databases that haven’t been fully integrated across your business’s system. This makes it difficult to access the right data when you need it, which becomes detrimental to your ability to extract meaningful insights, patterns or trends.

Security and Privacy with Data Operations

Keeping data secure is maybe the most important concern of a business that utilises big data. The wealth of information certain companies hold about their customers, such as credit card details or email addresses, makes them a primary target for online hackers and fraudsters.

If companies don’t manage their data properly – in particular if data silos become prevalent – they become less secure against cyber attacks.

Because of the challenges listed above, implementing a data operations strategy for analysing big data is crucial. Not only does it help you maximise your insights, but it’s necessary to ensure that unauthorised personnel or cyber criminals can’t gain access to private customer information.

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How can data silos be exploited by fraudsters?

Cyber criminals are getting smarter. They know where to look to covertly exploit vulnerabilities in an enterprise’s system. And data silos are one of the best trap doors a fraudster can find.

Often cyber security measures deployed throughout a system are not integrated with one another, meaning sophisticated attacks that span several areas of the network are harder to detect. So unless an organisation has the extensive resources needed to manually identify correlated threats, these kinds of attacks will likely go unnoticed.

Data silos often correspond with operational silos too, meaning management teams are less likely to have consistent security protocols across departments or communicate about potential threats.

Siloed data systems therefore both directly and indirectly cause siloed – and therefore weakened – cyber security solutions. Fraudsters, hackers and other malicious cyber criminals are aware of these weaknesses in company networks and commonly use them as a way to infiltrate, steal, and exploit people’s data.

That’s why it’s imperative to prioritise breaking down data silos as part of your cybersecurity strategy.

How can you combat data silos to reduce your cyber security threats?

Implementing a comprehensive security solution and consistent protocols at a company-wide scale is key to preventing silos from being created. Consolidating your security system, sharing data and resources, and providing the same online training across departments will help to eliminate data silos and optimise your cyber security.

This involves a lot of work identifying where silos are, auditing internal processes and structures, collecting and merging information systems, and encouraging a cultural shift in the workplace – but it’s absolutely imperative for any company working with big data.

Implementing a new cybersecurity solution won’t be achieved overnight. Bringing in an expert who has technical and industry knowledge can ensure you create a robust system that effectively reduces your online risk.

How does RiverSafe’s approach to Data Operations support this?

RiverSafe provides data operations solutions that can connect all of your data points seamlessly. Not only will we eliminate your existing silos, but we can help create better operational structures that better protect you from cyber threats.

Our unique delivery framework helps you get the maximum impact from our solution, so everyone in the company can minimise their risk and make the most of big data insights.

Get in touch with us at or complete the form below to speak to one of our experts today.


By Riversafe

Experts in DevOps, Cyber Security and Data Operations