Raw data is useless no matter how much of it you collect. Processing is what makes it meaningful.
Meanwhile, if you read our article on cybersecurity in hospitality, you know that sensitive information leaks can cost you a pretty penny. According to IBM, 4.35 million dollars is the average (!) cost of a security breach. Of course, such statistics can drive you away from taking advantage of your data using a software solution, especially if you need a third-party vendor to build one. So, the question is, how can you ensure secure data processing in outsourcing?
Well, let’s start with the basics.
What is data processing?
Data processing is the process of deriving insights from data. This task is typically implemented by a data scientist and consists of the following stages:
First up, you pull raw data from all available resources. It can be monthly metrics on user activity from your Google Analytics, customer reviews on your social media accounts, recordings of phone calls with clients, and so on. Since the collected data will directly affect the quality of your insights, make sure it’s relevant and sufficient.
Once you have all the necessary data, you need to increase its quality. Your task here is to scan your data for errors, duplications, and other imperfections to get rid of them. Also, watch out for incomplete data, complement it with missing data sets and remove irrelevant data.
Once you have clean, harmonized data sets, they are imported into the processing environment, such as a CRM or data warehouse. This stage typically involves converting the imported information into a format compatible with this environment and giving it a more efficient structure by sorting and indexing data.
Now, you actually transform the prepared data into insights. Small data sets can be processed manually with the help of SQL queries or Excel. But in all other cases, you won’t go without software solutions that use machine learning and deep learning algorithms. They can quickly sift through enormous amounts of data and see patterns where human analysts don’t.
5. Interpretation and visualization
But none of these efforts will bring you business value if your upper management doesn’t understand the insights that result from data processing. Be sure to translate your findings into a digestible format. Graphs, charts, diagrams, and other visualization means are your best friends here.
Ideally, the data processing lifecycle is iterative: the output produced from the interpretation stage can be used as input for a new iteration. To make it possible, all the processed data needs to be placed in a storage, so you can access and retrieve it easily whenever necessary.
As you can see, data processing is a labor-intensive task that requires relevant experience and expertise. And there’s another important issue: how do you make sure no data leaks or gets lost as you move it from one place to another?
But before we get into secure data processing, let’s take one step back and see how data security needs have changed as we’ve entered into the cloud computing era.
From servers to cloud computing: New data privacy threats
Back in the day, when local servers were the only decent option to store data, businesses had to struggle with numerous shortcomings of onsite data centers, such as access challenges, collaboration roadblocks, maintenance and scalability issues, and so on.
So, when cloud computing came into the picture and became commonplace, many companies were relieved. Dealing with large amounts of data became painless: data was easy to share and collaborate on in real-time, backups were automatic, and maintenance and scalability of the hosting infrastructure were now the responsibility of a cloud provider.
At the same time, using cloud servers for processing and storing data isn’t all roses, with security being the most pressing concern, according to Flexera. Take a look at some of the most common data security loopholes:
- Compromised credentials. Cloud accounts with weak passwords are traditionally an easy target for bad actors. Verizon’s report states that 81% of data breaches result from password issues.
- Misconfigurations. Sometimes, organizations simply fail to set up all the necessary security controls in their cloud accounts. This issue is more persistent than it seems: according to the SaaS Security Report, 89% of surveyed organizations consider misconfigurations one of the top three cyber threats.
- Unsecured APIs. Even if your cloud infrastructure has all the security controls in place to shield your data from cyber criminals, less protected APIs can serve as a gateway for unwanted invasion.
- Insider threats. Yes, this type of threat isn’t specific to cloud computing—on-premise data centers aren’t immune to dishonest employees, either. However, this fact doesn’t diminish the scope of the problem: a whopping 98% of organizations don’t consider themselves to be fully protected from insider cyber threats.
If left unattended, these and other loopholes can make your system vulnerable to a variety of threats, with ransomware attacks being the most common one. Just imagine: only in the first six months of 2021, internet users worldwide experienced more than 304.7 million attempted ransomware attacks.
But does this mean that you need to refuse all the merits of cloud computing and put up with the limitations of on-premise infrastructure for the sake of data security? Not at all. In fact, secure data processing in the cloud exists! Let’s take a look at its main principles.
Achieving data security in the cloud at all processing stages
Remember the stages of data processing we were talking about? There are ways to mitigate cloud security concerns at each of these stages:
- Secure data collection. When collecting data, pull it from trusted sources only. Also, make sure the connection is secured. Protocols like TLS/SSL will help safeguard your connection and rule out data interception. It’s also a good idea to restrict access to data and only provide it to the employees who need it. When you’ve collected the data, store it in an encrypted location.
- Secure data preparation. This stage involves the human factor, so ensure the data engineers and scientists who are going to clean up your data sets follow security guidelines: use trusted networks to transfer data and an approved set of tools to process it, only store the data on a secure corporate workstation and lock it when leaving, not store the data on personal unencrypted flash drives, etc.
- Secure data integration. Your data engineers should only use trusted tools for data conversion, formatting, and batching. And don’t forget about securing your connection with a TLS protocol.
- Secure data processing. The processing services and tools your employees use should be up to date with the latest security patches and secured with a proper access control level (ACL). This includes permission management and access monitoring.
- Secure data interpretation. There’s nothing new you can do to ensure data security when visualizing it: use proven tools for dashboards and data presentation, make sure they’re patched and up to date, and don’t allow employees to handle this data on their personal devices.
- Secure data storage. When selecting a storage for your data, make sure it’s encrypted, the ACL is properly configured, and the APIs are secured.
As you can see, many of these tips are based on encryption, access control, and security training for employees. Software outsourcing companies should know and practice all that. But do they?
Read also: Data Security Practices for Compliant and Secure Software Development
Secure data processing when outsourcing software development
You can safely process your data in the cloud if you follow all security measures solemnly. Still, there are cases when it doesn’t depend on you. Suppose there are no suitable data processing solutions on the market, and you can’t afford to build one in-house. In this case, you have no choice but to outsource the development to a third party. This, in turn, can put your sensitive data at risk.
How do you protect it? Generally, secure data processing in outsourcing rests on four principles.
Yes, you should take this into account even if your software development provider uses cloud servers to process your data. Just like traditional local servers, these are actually pieces of physical hardware prone to physical damage. Even the top cloud infrastructure providers aren’t immune to mishaps. For example, hurricane Sandy once took Amazon data centers offline, making some of the popular services of the tech giant unavailable. A reliable vendor should have a backup plan for such instances.
Are you using the IT infrastructure on the premises of your software development partner? Even more so. Check their physical security level. Make sure that they have a 24/7 security guard, card and number-pad access, fire alarms, and other measures that comply with international standards.
Make sure your vendor has the necessary technological safeguards in place to protect your data in transit and at rest. Evaluate how they prevent viruses, trojans, malware, and other cyber threats. Also, they should have an actionable plan to diminish the consequences of a cyberattack or data leakage.
And bear in mind that the cybersecurity landscape evolves quickly as cyber criminals continuously invent new ways to challenge security controls. This means that your data security needs will change with time. So, if it’s a long-term partnership, make these audits recurrent.
Don’t underestimate malicious or simply negligent insiders. Before you give the green light to your future partner, familiarize yourself with their security policy. Coherent and working, it should cover information protection, internet usage, passwords, system access, and other aspects. Besides, an ideal partner should follow the Principle of Least Privilege (PoLP)—only engineering team members who need your data to fulfill their tasks will be given access to it.
Even if your potential partner assures you that they have all the necessary safeguards and policies in place, it’s no more than just words, not guarantees, without legal backup.
So, before you share your confidential information with any vendor, familiarize yourself with their portfolio of compliances, making sure it covers the specifics of your niche, business, and location. For example, if you’re building a software solution that processes medical data, feel free to disregard vendors without HIPAA compliance. Or, if you’re working with sensitive information of European citizens, inquire if your partner complies with GDPR.
Also, be sure to sign all the necessary agreements. Of course, a non-disclosure agreement (NDA) is a must for every partnership that involves confidential data. You can sign it with every member of your software development team. You should also consider signing agreements that regulate data transfer. Besides, if your project involves processing data of EU citizens, you’ll need to have a Data Processing Agreement (DPA) on your “to-sign” list.
But what’s DPA, and why is it necessary to sign? Let’s unpack this below.
Data Processing Agreement
A Data Processing Agreement is a written agreement between a data controller (here: the company that outsources software development) and a data processor (here: a software development vendor). It lays out the requirements for secure data processing.
Sounds quite straightforward, right? Well, note that “data” and “data processing” have specific implications here. Within a DPA, the term “data” covers only personal information, namely, any information that can be used to contact, identify, or locate a person. As for “data processing,” it goes far beyond the business intelligence definition and stands for any action performed on personal data by a third party, including collection, recording, organization, retrieval, erasure, and beyond.
So, in other words, a DPA protects the personal data of EU citizens by ensuring that data processing activities and security measures fully comply with GDPR. The document includes the following elements:
- General information: key definitions related to personal data processing
- Responsibilities: details on how exactly the agreement parties share responsibilities for handling personal information
- Technical and organizational requirements: technical safeguards and procedures the data processor is expected to follow to ensure safe data processing
A DPA is essential for GDPR compliance. This means that whether you operate on the EU territory or your activity relates to processing the data of EU citizens, signing this document is mandatory whenever your project implies a third party accessing personal information. So, if you are subject to GDPR, be sure that your vendor will guarantee compliance.
Finding the right partner: Why Acropolium?
With a DPA, the likelihood that your sensitive information will remain intact throughout the entire project course is higher. Plus, it’ll help you stay GDPR compliant. Still, this document won’t fully spare you from the consequences of the data breach: as a data controller, you are liable for any data leaks, and your reputation is still at risk.
Meanwhile, the outsourcing market is brimming with vendors that take security lightheartedly, to say nothing about GDPR compliance. Some even don’t know exactly what a DPA is. So, how do you make sure that a software development service provider doesn’t take shortcuts when it comes to security and compliance?
Well, you can contact your potential tech partner and ask them about their data security and compliance practices. Still, if you are not tech-savvy enough to make expert conclusions from such an interview, you can safely open your browser and research the reputation of your potential vendor. Check their portfolio of projects, read reviews, analyze their social media pages, or contact their past clients if possible. And don’t forget to check their ratings at B2B research platforms before you sign any contracts.
If you go to Clutch or GoodFirms, you’ll find Acropolium among the top software development service providers listed there. But why do our clients trust us? First, our expertise is huge: we are keen on in-demand technologies, like AI, big data, cloud and serverless computing, and blockchain. Second, we have a proven record of successful projects across niches—many of them involve data processing. Third, the security of your confidential data is our top priority, which means that:
- We constantly monitor the cybersecurity landscape, making sure that we have all the necessary safeguards in place for guaranteed protection.
- All our projects begin with signing an NDA with every development team member.
- If you are GDPR compliant, you’re in the right place. Having numerous GDPR projects under our belt, we won’t get down to the implementation without signing a DPA that fully protects your interests. We are constantly examining GDPR laws to ensure that we use best practices.
- We regularly educate our experts on topics related to sensitive data.
So, if you have a data processing project on your mind, we’ll help you bring it to life with minimal risk to your data. And besides, we support different outsourcing models, including the Software Development as a Service Subscription model, so you can select the option that suits you best.
Data leaks can cost you a fortune. They might incur GDPR fines, ransomware payouts, “exile” from application markets, let alone a ruined reputation. These threats can make you hesitant to implement a project that involves sensitive data processing.
Still, cybersecurity experts know what they’re doing, and much depends on your care and caution. So, don’t let fears affect your business decisions. Follow our data protection tips, and if you need software development assistance, feel free to reach out to Acropolium.