Cloud Data Security

What is Cloud Data Security? Your Complete Guide

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What is Cloud Data Security? Your Complete Guide

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What is Cloud Data Security? A Definition

Why is everyone talking about cloud data security today? The first wave of digital transformation focused on moving software workloads to SaaS-based applications in the cloud that were easy to spin up, required no new hardware or maintenance, and started with low costs that scaled with use. Today, the next generation of digital transformation is focused on moving the data itself — not just from on-premises data warehouses to the cloud but from other cloud-based applications and services into a central cloud data warehouse (CDW) like Snowflake. This consolidates valuable and often very sensitive data into a single repository with the goal of creating a single source of truth for the organization.

Cloud data security is focused on protecting that sensitive data, regardless of where it’s located, where it’s shared or how it’s used. It uses role-based data access controls, privacy safeguards, encrypted cloud storage, and data tokenization among other tools to limit the data users can access in order to meet data security requirements, comply with privacy regulations and ensure data is secure.

3 Benefits of Cloud Data Security

Cloud data security confers powerful benefits with almost no downsides. In fact, the biggest risk of cloud data security is not doing it.

  • Improve business insights: When applied correctly, cloud data security enables data to be distributed securely throughout an organization, across business units and functional groups, without fear that data could be lost or stolen. That means you can share sensitive PII about customers with your finance teams, your marketing teams and even your sales teams, without worry that the data might make its way outside the company. You can gather information from various in-house and in-cloud business tools such as Salesforce or another CRM, your ERP, or your marketing automation solution into one centralized database where users can cross check and cross reference information across various data sources to uncover surprising insights.
  • Avoid regulatory fines: It’s not just credit card numbers or health information that companies need to worry about anymore – today, practically every company deals with sensitive, regulated data. Personally Identifiable Information (PII) is data that can be used to identify an individual such as Social Security number, date of birth or even home address. It’s regulated by GDPR in Europe and by various state regulations in the US. Although the regulatory landscape is still patchy in the US, all signs point to a federal level statute or new regulation that will lay out rules for companies across the country coming very soon. For companies that want to get ahead of the issue, making sure their cloud data security meets the most stringent requirements is the easiest path. This can help a company ensure its meeting its obligations and reduce risk of fines from any regulation.
  • Cultivate customer relationships: In a 2019 Pew Research Center study 81% of Americans said that the risks of data collection by companies can outweigh the benefits. This might be because 72% say they benefit very little or not at all from the data companies gather about them. A McKinsey survey showed that consumers are more likely to trust companies that only ask for information relevant to the transaction and react quickly to hacks and breaches or actively disclose incidents. These also happen to be some of the requirements of data privacy regulations – only gather the information you need and be upfront, timely and transparent about leaks. Companies can’t continue to gather data at will with no consequences – customers are awake to the risks now and demanding more accountability. This gives organizations a chance to strengthen the relationship with their customers by meeting and exceeding their expectations around privacy. If personalization creates a bond with customers, imagine how much more powerful that would be if buyers also trust you. Organizations that focus on protecting customer data privacy via a future-focused data governance program have an opportunity to take the lead in the market.
Cloud Data Security

Cloud Data Security Challenges

Although cloud data security is a new area of concern, many of the biggest challenges are already well known by companies focused on keeping data safe.

  1. Securing data in infrastructure your company doesn’t own: With so much data moving to the cloud, yesterday’s perimeter is an illusion. If you can’t lock data down behind a firewall, and guess what, you can’t, then you’re forced to trust your cloud data warehouse. These facilities are extremely secure, but they only cover part of your security needs. They don’t manage or control user data access – that’s left to you. Bad actors don’t care where the data is – in fact, cloud data warehouses that consolidate data from multiple sources into a single store make a compelling target. Regulators don’t care where data is either when it comes to responsibility for keeping it safe: it’s on the company who collects it. Larger companies in more regulated industries face very punitive fines if there’s a leak—which can lead to severe consequences for the business.
  2. Securing data your team doesn’t own: From a security perspective, it’s difficult to protect data if you don’t know what it is or where it is. With various functional groups across companies making the leap to cloud data warehouses on their own in order to gain business insights, it’s difficult for the responsible groups such as security teams to be sure data is safe.
  3. Stopping privileged access threats: When sensitive data is loaded to a CDW there’s often one person who doesn’t really need access, but still has it: your Snowflake admin. If your company is like Redwood Logistics, uploading sensitive financial data in order to better estimate costs, you really don’t want your admin to have access – and usually, he doesn’t either! Even if you trust your admin and you probably do, there’s no guarantee his credentials won’t get stolen and no upside to him or the business to allowing that access. This leads into our next challenge:
  4. Stopping credentialed access threats: Even the most trustworthy employees can be phished, socially engineered or plain have their credentials stolen. Despite the training companies have done to educate users about these risks, the credentialed access threat continues to be one of the top sources of breach in the Verizon Data Breach Investigations Report, for the sixth year in a row! ALTR’s James Beecham asks year after year: “Why Haven’t We Stopped Credentialed Access Threats?” We know how – even when humans are fallible there is technology that can help.
  5. Using data safely in Business Intelligence tools: One of the key goals to consolidating data into a centralized CDW is to enable business intelligence access. BI tools like Tableau, ThoughtSpot and Lookr depend on access to all available data in order to provide a full 360 view of the business.  When the data can’t be utilized securely in these tools, it often results in security admins making the call to leave that data out of the equation, creating a broken view of the business.
Cloud Data Security

Cloud Data Security Best Practices

There are a few best practices every organization should incorporate into their successful cloud data security program:

   1. Keep your eye on the data - wherever it is

This shift to the cloud really requires a shift in the security mindset: from perimeter-centric to data-centric security. It means CISOs (Chief Information Security Officer) and security teams will have to stop thinking about hardware, data centers, firewalls, and instead focus on the end goal: protecting the data itself. Responsible teams need to embrace data governance and security policies around data throughout the organization and its data ecosystem. They need to understand who should have access to the data, understand how data is used, and place relevant controls and protections around data access. In fact they could start with a data observability program in order to understand what normal data usage looks like so they're better able to identify abnormal.

   2. Empower everyone to secure cloud data

We often hear “security is everyone’s responsibility.” But how could it be when most are left out of the process? While data is a key vulnerability for essentially every company, until recently most companies didn’t want to acknowledge the risk. Now, with a new data breach announcement every few weeks, the problem is impossible to ignore. When marketing teams are using shadow cloud data warehouse resources instead of waiting for security or IT teams to vet the solution for security requirements, it’s easier to make sure data owners have the means to protect the data themselves. Instead of governance technologies based on legacy infrastructure that not only require big investments in time, money, and human resources to implement, but also expensive developers to set up and maintain, democratize data governance with tools that allow non-coders to rollout and manage the data security solution themselves in weeks or even days.

   3. Add cloud data security checks and balances to your cloud data warehouse

To protect data (and your Database Administrator!) from the risk of sensitive data, put a neutral third party in place that can keep an eye on data access - natively integrated into to the cloud data platform yet outside the control of the platform admin. This separation of duties should make it impossible to access the data without key people being notified and can limit the amount of data revealed, even to admins. It can include features like real time alerts that notify relevant stakeholders at the company whenever the admin (or any user for that matter) tries to access the data. If none of the allowed users accessed the data, they’ll know unauthorized access has occurred within seconds. Alert formats can include text message, Slack or Teams notifications, emails, phone calls, SIEM integrations, etc. Data access rate limits that constrain the amount of de-tokenized data delivered to any user, including admins, also limit risk. While a user can request 10 million records, they may only get back 10,000 or 10 per hour. This can also trigger an alert to relevant stakeholders. These features ensure that no single user has the keys to the entire data store – no matter who they are.  

   4. Always assume credentials are compromised and cloud data is at risk

Knowing that the easiest and best ways to stop credentialed access threats are undermined by people being people, we’re simply better off assuming all credentials are compromised. Stolen credentials are the most dangerous if, once an account gets through the front door, it has access to the entire house including the kitchen sink. Instead of treating the network as having one front door, with one lock, require authorization to enter each room. This is actually Forrester’s “Zero Trust” security model – no single log in or identity or device is trusted enough to be given unlimited access. This is especially important as more data moves outside the traditional corporate security perimeter and into the cloud, where anyone with the right username and password can log in. While cloud vendors do deliver enterprise class security against cyber threats, credentialed access is their biggest weakness. It’s nearly impossible for a SaaS-hosted database to know if an authorized user should really have access or not. Identity access and data control are still up to the companies utilizing the cloud platform.  

Cloud Data Security

Key Components of Cloud Data Security Solutions

An effective cloud data security solution includes these key components:

  • Knowing where your data is and categorizing what data is sensitive: With data often spread throughout an organization’s technology stack, it can be challenging to even know all the various places sensitive data like social security numbers are stored. Solving this issue often starts with a data discovery and data classification solution that can find data across stores, group information into types of data and apply appropriate tags.
  • Controlling access to sensitive data: In today’s data-driven enterprises, data is not just used by data scientists. Everyone from marketing to sales to product teams may need or want access to sensitive data in order to make more informed business decisions but not everyone will be authorized to have access to all the data. Making sure you have the ability to grant access to some users but not others, or allow access to some roles but not others, in an efficient, scalable and secure way is one of the most important components of cloud data security.
  • Putting extra limits on sensitive data access: Data security doesn’t have to be either/or. With data access rate limits, users can be prohibited from gaining access to more data than they should reasonably need. This can stop bad actors with credentials from downloading the whole database by setting rate limits per user or per time period, ex: 10,000 records in 1 hour vs 1M.  
  • Securing sensitive data with encryption or tokenization: Encryption is one cloud data security approach that is highly recommended by security professionals. However, it does have weaknesses and limitations when it comes to utilizing data in the cloud. Tokenization can enable data to be stored securely yet still be available for analysis.


There’s no chance of reversing the migration of data to the cloud and why would we want to? The benefits are so staggering, it’s well worth any challenges presented. As long as cloud data security is built in as a priority from the start, risks can be mitigated, and the full power and possibility of a consolidated Cloud Data Warehouse can come to fruition.  

See how ALTR can help automate and scale your cloud data security in Snowflake. Get a demo!  

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