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Is Your Data Safe? How to Assess Your Data Risk - Part 1

Christophe Toum
Talend

Data is one of a company's most valuable assets — but Talend's recent Data Health Survey found only 40% of executives always trust the data they work with.

Today, we have codes and inspections for physical infrastructure, satisfaction surveys for employees, and up-time monitors and stability tests for websites. But are we doing everything we can to understand the degree to which our data is exposed to risk?

There's more to security than protecting yourself from hackers. On one end of the spectrum, you have those big exposures to governmental regulations and security breaches that can shake an entire organization. But even small things — like a little bit of bad data entering the system — can cause a trickle down effect that impacts every department.

We could all be doing a better job of assessing (and mitigating) risk to our data. The key is to start small: just make sure that you have the right data in the right place.

Then you want to make sure that the right people have access to the data and the wrong people don't have access to the data.

Once you have that covered, and you've defined processes for keeping your data clean and standardized, then you can start focusing on making that a daily practice. All it takes is the right combination of people, processes and technology.

What Do We Mean by "Risk?"

When most people think about the risks associated with data, they immediately recall the headline-grabbing data breaches that seem to flood our news feeds with alarming regularity.

But it doesn't take an epic leak affecting millions of users to have serious consequences for most companies. Even a handful of exposed records could have serious legal, financial and reputational repercussions. Fines for GDPR violations alone can run in the millions of dollars, to say nothing of the incalculable cost of losing consumer trust in an increasingly connected and competitive marketplace.

How do these breaches happen?

It can be something as simple as the right data in the wrong place. So much of our conversation about security centers around personally identifiable information (PII). If PII data isn't identified or isn't in the right field — for example, payment information erroneously mapped to an unprotected field and viewed by unauthorized individuals — you could be at risk of exposing some very sensitive information.

But external risks aren't the only dangers we should be worried about. A few years ago, IBM famously calculated that bad data costs US businesses over$3 trillion per year. This is death by a thousand cuts, parceled out in seconds, minutes and hours lost to manual data correction, re-running suspect reports and pursuing strategies and programs that were originally scoped based on data that was later revealed to be faulty.

Of course, the volumes of data we must deal with has grown by over 400% since IBM released that study — and it's only growing.

So how much could we be losing today?

And how much do we stand to lose over the coming years?

Taking all these dangers into account, one thing is clear: no company can afford to expose its data to risk.

Go to: Is Your Data Safe? How to Assess Your Data Risk - Part 2

Christophe Toum is Senior Director of Product Management at Talend

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Is Your Data Safe? How to Assess Your Data Risk - Part 1

Christophe Toum
Talend

Data is one of a company's most valuable assets — but Talend's recent Data Health Survey found only 40% of executives always trust the data they work with.

Today, we have codes and inspections for physical infrastructure, satisfaction surveys for employees, and up-time monitors and stability tests for websites. But are we doing everything we can to understand the degree to which our data is exposed to risk?

There's more to security than protecting yourself from hackers. On one end of the spectrum, you have those big exposures to governmental regulations and security breaches that can shake an entire organization. But even small things — like a little bit of bad data entering the system — can cause a trickle down effect that impacts every department.

We could all be doing a better job of assessing (and mitigating) risk to our data. The key is to start small: just make sure that you have the right data in the right place.

Then you want to make sure that the right people have access to the data and the wrong people don't have access to the data.

Once you have that covered, and you've defined processes for keeping your data clean and standardized, then you can start focusing on making that a daily practice. All it takes is the right combination of people, processes and technology.

What Do We Mean by "Risk?"

When most people think about the risks associated with data, they immediately recall the headline-grabbing data breaches that seem to flood our news feeds with alarming regularity.

But it doesn't take an epic leak affecting millions of users to have serious consequences for most companies. Even a handful of exposed records could have serious legal, financial and reputational repercussions. Fines for GDPR violations alone can run in the millions of dollars, to say nothing of the incalculable cost of losing consumer trust in an increasingly connected and competitive marketplace.

How do these breaches happen?

It can be something as simple as the right data in the wrong place. So much of our conversation about security centers around personally identifiable information (PII). If PII data isn't identified or isn't in the right field — for example, payment information erroneously mapped to an unprotected field and viewed by unauthorized individuals — you could be at risk of exposing some very sensitive information.

But external risks aren't the only dangers we should be worried about. A few years ago, IBM famously calculated that bad data costs US businesses over$3 trillion per year. This is death by a thousand cuts, parceled out in seconds, minutes and hours lost to manual data correction, re-running suspect reports and pursuing strategies and programs that were originally scoped based on data that was later revealed to be faulty.

Of course, the volumes of data we must deal with has grown by over 400% since IBM released that study — and it's only growing.

So how much could we be losing today?

And how much do we stand to lose over the coming years?

Taking all these dangers into account, one thing is clear: no company can afford to expose its data to risk.

Go to: Is Your Data Safe? How to Assess Your Data Risk - Part 2

Christophe Toum is Senior Director of Product Management at Talend

Hot Topics

The Latest

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...