How to Deal With Too Much Data: Data Minimalism

What Strategies Can Help You Handle Too Much Data?

Deal With Too Much Data –  is one of the most valuable tools of modern business operations. It empowers objective decision-making and enables owners and managers to extract more value from every component of the organization.

If you perform appropriate data gathering and analysis, you can increase your understanding of your business environment by a significant amount – and thereby gain a considerable competitive edge. Additional data implies your edge hypothetically expands, which is why so many companies have dramatically increased their investment in data generation and analytics.

But could there be such a thing as deal with too much data?

What is “Too Much” Data?

More data is usually a good thing. Think about this in your own life.

If you’re trying to decide which mustard to buy, and all you know is the price of each option, you won’t be able to make a good decision. But if you also know the volume, taste, reviews, and ingredients of your options, you can make a much more informed decision.

There comes a point where the data becomes “too much,” however. Here are some of the main reasons:

• Signal versus noise. In any set of data, we can segregate information between the broad categories of “signal” and “noise.” Imagine you have a high-resolution digital picture of a tree. There might be 4 million pixels in this photo, but fewer than a million actually constitute the tree. The rest are merely the background, and probably aren’t worth including.

Pixels that make up the tree are the signal you’re looking for, and the other pixels are primarily noise. As your data set gets bigger, it becomes more challenging to differentiate between the two; you run the risk of misrepresenting the noise as the signal, or miss the signal entirely.

• Wasted resources. Big data also means wasting more resources to gather and process the information. Given enough time, attention, and money, you can hypothetically process any volume of it. But if you spend too many resources before arriving at meaningful conclusions, you’ll be wasting your assets.
• Misleading conclusions. It’s also possible for misleading conclusions to emerge from exceptionally large data sets. For example, small mistakes in data production or aggregation may be magnified, and confirmation bias becomes more likely. You can control for this, but again, it’s going to cost you.

How to Deal With Too Much Data

You should know how to guard against the risk posed by too much data.

• Set clear KPIs and benchmarks. KPIs and benchmarks are your north stars. If you know exactly what you’re looking for, and which metrics you require to achieve your goals, you will cut through all the noise, no matter how much, and come up with a clear picture of what’s happening.
• Focus on quality over quantity. When you gather and process data, focus on quality over quantity. There could be dozens of details and trends you could measure with respect to user behavior on your website, but only a few of those data points are going to be worth exploring. Make sure your data is accurate, consistent, and tied directly to your business goals.
• Cut the vanity metrics. Too often, firms get bogged down with vanity metrics. These are measures that seem cool or make you feel productive, but don’t lead to better decision-making. Nor are they an adequate indicator of overall performance. An example might be the total number of followers on social media. Cut these out when you find them.
• Automate whatever you can. Automation is incredibly valuable for most organizations. It’s even more precious for processing and analyzing data. If you can reduce the amount of time you spend on data analytics, you may worry far less about wasting resources.
• Utilize AI. Artificial intelligence (AI) has progressed substantially in recent years. It’s now capable of analyzing even the largest data sets with remarkable effectiveness. Given the appropriate AI tools, the risks of too much data will fade.
• Practice smart hiring. There are nearly 100,000 data analyst positions in the United States, and even more jobs that require some degree of skills in data analytics for the performance of daily duties. You have plenty of candidates to choose from, so practice smart hiring to make sure you put the right people to work on your data challenges.
• Tie data to actions and decisions. Finally, remember that your data is valuable only if it’s fully actionable. All the data you gather and analyze should be directly tied to your actions and decisions.

Most organizations don’t have to wrestle with the problem of too much data because practically speaking, an absurd amount of data is necessary to qualify as “too much.” Thankfully, you have plenty of strategies to handle these issues so you can continue crunching the numbers and making better business decisions.