Modern businesses rise and fall based on the strength of their insights. What does gaining and capitalizing on such insights take? Vast quantities of big data that’s ready for the taking! We’re in the midst of a modern-day gold rush where everyone is scrambling to soak up as much data as possible in hopes of devising a winning strategy.
While neglecting this seemingly inexhaustible resource would be foolish, savvy businesses need to ensure the data they’re gathering is up to par. This article will introduce you to the most pressing challenges you’ll face when striving to keep the data relevant, unbiased, well-organized, and fruitful.
Importance of Quality Data
Big data is valuable because of its predictive capabilities. Timely and correct data drives beneficial business decisions or can benefit machine learning and automation efforts. Incomplete, inconsistent, and bad data can undermine all your other efforts, so ensuring its quality is a top priority.
Faulty data ranges from innocuous mistakes like typos and duplicate entries to intentional misinformation someone could use to poison an AI’s training set. The best way to tackle the issue is to establish a procedure for filtering, categorizing, and generally manipulating data.
Companies need skilled data scientists and engineers to do so. Such positions are in high demand, yet the availability of skilled talent is scarce and unreliable. Even if you have a healthy employee pool, you still need a robust data governance policy that outlines proper collection, manipulation, and access procedures.
Disparate Sources & Integration Challenges
Big data comes in various formats and is extractable in different ways. For example, a business can generate it on its own by sending out surveys or extracting the data accumulated by its CRM. Exponentially, more information is available on the internet at large. Think social media posts, product listings, reviews, images, videos, etc.
The vast majority of this data is unstructured, and much of it is qualitative rather than quantifiable. The challenge anyone who collects it faces is twofold. On the one hand, the issue is technical since you need a unifying format that bridges the gap between different data types while also being compliant with analytics tools.
On the other, data with the same format can come from diverse sources and offer different insights. It is useful only if you can link it to existing data and the broader data collection & processing strategy you’re pursuing.
Tool Selection
Making sense of petabytes of data with a steady stream of more on the way is impossible for humans alone. Appropriate tools exist that make big data processing achievable and insightful. However, finding the right ones isn’t always a clear-cut task.
The tools’ accessibility depends on the skillsets of the people handling their results. Companies without dedicated data science teams will want to take advantage of ready-made, intuitive solutions like web scrapers. When utilizing web scrapers, especially for sensitive data extraction or to bypass geographical restrictions, consider augmenting them with dedicated proxies. They enhance security and anonymity, ensuring a more robust and reliable data-gathering process.
Providing scrapers with instructions on what to look for is straightforward, and creating an organized database populated with relevant data doesn’t take long. Augmenting them with proxies ensures the process goes more smoothly while allowing access to data that might otherwise be geographically restricted.
The right analytics tools need to be able to convert usable data scrapers, surveys, and other collection tools create and convert them into actionable insights. This is only possible if you understand how to recognize and use such insights to further your business goals.
There’s also the matter of cost & scalability. Even though you should be dealing with distilled and categorized data, storage costs can balloon as your data-gathering operation ramps up. Likewise, any collection, analytics, and storage providers also need to offer flexible plans capable of dealing with a sudden need for expansion or retraction.
Ethical Concerns
Collecting and benefitting from big data’s insights comes with ethical considerations companies need to be aware of.
Even the most callous company not interested in upholding the rights of those who contributed the data must account for bias. Much of big data comes from human interaction with digital systems. As soon as humans are part of the equation, the data you’re working with may be under the effects of historical, racial, and other biases that even the people contributing their data might not be aware of.
Then there’s the matter of consent. Ideally, all the data you gather should come through informed consent. Much of it is available publicly, and users give their consent via EULAs and other agreements. Still, many may not realize what they’ve tacitly handed over.
Equally important is data security. Once you’re working with sensitive data like financial, medical, or personally identifiable information, you have a responsibility to safeguard it. Criminals are devising increasingly more clever ways to get at such data. Unsurprisingly, the frequency and costs of data breaches keep rising in turn.
In enhancing data security, Virtual Private Networks (VPNs) are essential. They encrypt data transfers, ensuring sensitive information remains protected from unauthorized access. Additionally, VPNs help mask IP addresses, increasing anonymity and safeguarding against cyber threats. Integrating this tool, for which you can find a suitable provider in a VPN comparison table, not only boosts your defenses but also highlights your dedication to ethical data management by prioritizing privacy and security.
Conclusion
Big data and the ways businesses can leverage it have created quite the buzz. As tempting as jumping right in sounds, taking steps to ensure the veracity and relevance of the data you collect first will pay off. We hope this article will bring you a step closer to getting the most out of it. Here’s to unlocking the true potential of your data and propelling your business into the future.
