DataOpsZone

If you’re like most data scientists, scoping projects probably isn’t your favorite part of your job. Scoping projects can often feel like a mix between tedious busywork meant to placate executives and wildly guessing. Chances are, you’ve had projects in the past totally miss their scoping requirements, only to see no negative side effects. Feeling like your work is meaningless, tedious and baseless is a recipe for frustration, no matter your profession. For data scientists, who are used to measuring things to determine their efficiency, it’s excruciating.

Fortunately, it’s possible to get better at scoping your projects. Project scoping is never going to go away, and despite what it might feel like, it’s not meaningless. Project scoping helps decision-makers determine how to prioritize projects for an organization. Doing it well means both that the most important projects receive the attention they need, and also that you’re more likely to be successful when you embark on a new project. In this post about how to scope a data engineering project, we’ll walk through a detailed guide on what you need to understand.

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Do you know the biggest challenge companies face? It’s maintaining a large information base. Too much information compromises data flow. But it’s important to manage the information at hand. A company has to succeed in managing data well. Only then can the employees make the right decisions. That’s where data lifecycle management comes in. What is data lifecycle management, you ask?

No matter how important data is, it loses its relevance over time. After all, no information can hold the same relevance for eternity! You have to manage the data to make the most out of it. But before we you can do that, it’s important to understand the data lifecycle.

In this post, we’ll take a detailed look into data lifecycle management (DLM), including the different phases of DLM and best practices. We’ll also highlight the importance of managing the data lifecycle in a company. So, let’s dive into the details.

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Businesses across all industries are racing to embrace digital transformation. At the same time, serious dangers in the form of data security risks lurk in the shadows.

Each day, businesses face a multitude of cyber threats from sophisticated hackers and bad actors. As for the consequences of enduring a cyberattack? They’re severe. According to one recent IBM study, the average U.S. data breach costs upwards of $8.19 million.

Think a data breach won’t ever happen to your company? Think again. Hackers frequently target even the most sophisticated organizations. Companies like Uber, Experian, Sony, Anthem, and Target have all been attacked in the past few years.

Chances are that your company has far fewer resources than any of these five. In that light, your business is probably even more vulnerable than they were.

When a hack occurs, immediate financial losses are only one piece of the puzzle. Data breaches are extremely disruptive to business. If your customer finds out that their data has been stolen, there’s a high probability that they will be hesitant to transact with you down the road. What’s more, you could also have your intellectual property (IP) stolen, leading to even greater losses in the long term.

If you’re concerned about the data security risks that your business faces, you’re not alone. A recent study revealed that 44% of U.S. CEOs feel that the risks involved with digital adoption are preventing their businesses from moving forward. Companies are literally chained to their old ways because they aren’t sure how to protect themselves against modern threats.

Before we examine what you can do to reduce the likelihood your business suffers a data security setback, let’s take a step back and get our definitions straight.

Continue reading “What Are Data Security Risks? 5 You Need to Know About”