It’s no secret that more companies are moving their data to the cloud. As of 2023, 60% of all corporate data will be stored in the cloud.
In the days before cloud storage, you knew where your data was at all times. There was a large data center with many cages and rows of servers housing and processing the data for the business. Companies ensured data did not leave the environment for security reasons, so keeping the data within the enterprise network was essential.
Today, data can live in three places: on-premise, in the cloud, or in a SaaS platform, most of which are cloud-based. Most companies today use a hybrid approach. Even if a company is 100% cloud-based, it also likely has many apps in SaaS applications.
Where is your data? What are the SLAs and rules for exporting your data from the SaaS providers? And more importantly, how secure is your data?
What Is Cloud Storage?
A cloud-based approach to data storage means you trust a platform like AWS, Google Cloud, or Microsoft Azure to house your data in a seemingly infinite warehouse in the virtual sky. (Many think that cloud capacity is endless, but it is not; as a case in point, Microsoft, Amazon, and others have run out of resources in specific regions or data centers.)
Enterprises are focused on data security with ISO 27001 and SOC-2 compliance, and they feel comfortable collecting more new data elements because cloud storage can expand more easily than on-premise.
The problem is, there’s a cost that comes with that – but that’s the subject of another article.
So, if you have opted for cloud storage, I will ask again: where is your data?
In numerous conversations with clients of my company, Fortified, I’ve noticed that enterprises generally have no clue how much data they have, what data they have, where their data is, and what it’s costing them to store it.
The reason for this is pretty straightforward: data doesn’t exist in one place.
Putting Data in Perspective
Think about this: 90% of the Fortune 500 companies leveraged Salesforce to manage their business relationships in 2022. These include Spotify, Amazon Web Services, Toyota, Walmart Inc., and McDonald’s, although the largest segment of Salesforce customers is smaller companies with $1M – $10M in revenue.
This means valuable customer data for these behemoths and many smaller businesses is in Salesforce. That’s one external SaaS app. Companies use an average of 80 external SaaS apps. So that’s 79 more places where their data is.
What’s more, as part of their Enterprise Data Strategy, most organizations are extracting data from SaaS apps like Salesforce to import into their own data lake or data warehouse for data analytics, creating yet another version of the same data.
Many of these SaaS platforms charge by the user or by a model combining users and consumption. What would happen if they charged solely based on consumption?
Think about your Netflix subscription, which is per user. If they switched to a consumption model and only charged you for the content you consume on their channel, how likely would you be to give it up? Before missing out on Season 3 of Bridgerton, you would probably try to limit your consumption by using less of the service.
No one is currently trying to limit their data storage. Why? The popular misconception is that it’s cheap and endless, so we don’t know what and how much we are storing at the enterprise level. We’ve created a generation of data hoarders because many enterprises believe that one day, the data will provide some value.
So, Once Again, Where Is Your Data?
If you’re doing business in the 2020s, your data is likely not in your office (on-premise). For one thing, your company may not even have an office anymore.
Imagine you must delete a data record – someone wants to opt out of your communications. By law, you have to remove this person from your marketing emails. How easily can you find their data record in 80 locations or “data houses”?
How can you possibly know what’s in each data house? How can you know which records you need to retain and which have value, not just today but in the future? These are the questions that organizations need to start asking about their data.
Suppose we truly want to comply with GDPR, the data privacy laws. In that case, we need to know where each piece of data is for each individual – including Excel files, databases, within your four walls, external systems, internal systems, and everything in the cloud.
Most of the databases belong to third-party applications that were written without native archive or purge capabilities. Hence, this makes it a challenge for enterprises to easily remove an individual’s data. These databases then have backups going back seven years, which also contain these personal records.
All this record-keeping comes at a cost: a cost of non-compliance as well as a financial cost.
Each company’s data estate is like a ball of yarn that needs to be unraveled. Providing visibility into where all that data is and what it’s costing you and identifying what has value will mean the difference between those companies that can control costs, increase efficiency, and comply with global privacy laws and those that falter under the weight of their own data troves.
Every time your organization signs up for a new platform, you create a unique data footprint. Think of your footprint as well. How many apps do you have on your smartphone? What data does each of these applications store? That means they have your data, even if it’s just an email address and most of the time, it’s much more than that.
A New Mindset for Data
What is your Enterprise Data Strategy for managing all your data? How are you managing and implementing the Data Lifecycle at your company? If you don’t have the answers just yet, it’s ok.
If you’ve read this far, it means you understand the problem and the need to tackle these issues head-on now before the costs—in consumer trust and financial terms—skyrocket. The pace of data acquisition and creation is only going to increase, so we need to get a plan in place and manage it – yesterday.
Like so many other topics I’ve written about, it all starts with a change in mindset. This starts at the top and needs to be communicated to every team that touches data as well as every new hire so that it becomes part of the company’s DNA.
If we adopt a mindset of efficiency and continue to focus 80-90% on innovation and the future, with a 10-20% focus on the past or tech debt, including all the code that’s in production, all the data in our various data houses and data lakes, and all of the systems we currently use to measure impact and costs, this will go a long way toward being able to answer the question where is our data with confidence.