Published On: August 26th, 2020Categories: Data GuideBy 3.9 min read

Take control of your data.

Take control of your data

Good quality data is essential for meaningful and actionable outputs from AI and ML algorithms, but its use doesn’t stop there. In subsequent sections, we’re going to focus on exactly how poor quality data leads to bad outcomes for AI and ML, but here we’re looking at the wider picture. Keep reading to take control of your data.

Security risks for big and small companies

Having control over your data is essential for robust security. How will you know when your data has been breached if you are not 100% clear on where your data is and how it is being utilized? No company is immune to cyberattacks, especially today. Data breaches and cyber-attacks are happening at an alarming rate all over the world. It seems that as soon as we advance our detection and prevention techniques, the bad actors also advance their methods of intrusion. It’s become a constant cat and mouse battle for data. Why? Because data is extremely powerful in the modern age.

Money is often the aim behind data breaches but not always. Sometimes the goal is to gather intelligence and steal ideas. Often companies mistakenly think they are either too big or too small to be targeted by cybercriminals. The truth is, cybercriminals are indiscriminate. Small companies are often the target of ransomware or malware attacks simply because their security is often weaker. But their data is just as important to the company as a large company’s data is to a large company.

If you are a small company and all of your systems become locked (you have no control over your data), this can have devastating consequences. In fact, one study found that approximately 60% of small businesses close within 6 months of being hacked[2]. With small companies, it’s often a numbers game for the hackers. The more companies they target with phishing emails or malware attacks, the higher the chance that they will be successful in their malicious goals.

In large companies, security tends to be much tougher, making it more difficult for cybercriminals to successfully hack the company. However, the rewards of being successful are much greater. Large companies have much larger sets of data and potentially sensitive intellectual property.

Establish a process and choose the right tool

To build a successful company that lasts and outperforms its competition, you must have a data-driven and data-centric approach to all areas of your business. Whether it’s data security, transformation, business intelligence or anything else, data management is key. To do this successfully, you need to ensure that you are in control of your data. This means you are in control of how your data is used and the quality of your data. Sounds like a challenge? One important part of getting on top is to ensure that you have a well thought out process for Data Governance and the right tools to support this.

The answer is Data Governance

With a modern, fully-automated data intelligence platform such as NodeGraph, you get a full insight into your entire data landscape. You have full control and understanding of your data, all the way down to the individual fields. All dependencies, transformations, expressions, data sources used, BI tools and so on, are right in front of you. You become empowered to make the right business decisions through the technology you choose to support your data journey.

Read the full guide

Access the full guide and learn about the importance of high-quality data and the harm that can come from poor quality data, as they are used in AI and ML.

The guide covers

An overview of the current data landscape
The relationship between AI and data quality
How bad data harms AI and ML
How to achieve high data quality
Data quality and ROI

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