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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

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E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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The 2025 Catchpoint SRE Report dives into the forces transforming the SRE landscape, exploring both the challenges and opportunities ahead. Let's break down the key findings and what they mean for SRE professionals and the businesses relying on them ...

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AWS is a cloud-based computing platform known for its reliability, scalability, and flexibility. However, as helpful as its comprehensive infrastructure is, disparate elements and numerous siloed components make it difficult for admins to visualize the cloud performance in detail. It requires meticulous monitoring techniques and deep visibility to understand cloud performance and analyze operational efficiency in detail to ensure seamless cloud operations ...

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