Top 5 Big Data Mistakes

The benefits of Big Data are inevitable. Are there pitfalls? Sure. Avoid these top 5 mistakes and avoid being jeopardized in your journey of using big data.

Digital Analytics
-
7 min
Digital Analytics
/
Top 5 Big Data Mistakes

Big data has become essential for companies working in competitive industries. Simply harnessing data, however, doesn't mean you use the information well.

Make sure you avoid these top five big data mistakes to improve your business operations, insights, and security.

Choosing the Wrong Data Storage System

Data storage options have changed a lot over the last few decades. You might still refer to your system as a "database," but it's probably a data warehouse or data mart.

A data warehouse works well for storing structured data from a relatively small number of sources. A data mart makes a great option for departments that need to store internal data.

Neither option does an excellent job of storing some types of information, though.

Far too many companies don't understand that the data warehouses they use to store customer-data data aren't appropriate for storing videos, text, and images.

If you don't know which data storage system suits your needs, talk to a data professional for guidance.

Storing All Data On-Site

While you might see some advantages from on-site data storage, keeping all of your information on-site opens your business to several risks.

For example, any disaster, including natural disasters like an earthquake or local disasters like a busted water line, could destroy your precious data. Storing data to the cloud eliminates this risk.

Storing data in the cloud also makes it easier to access. The Covid-19 pandemic increased cloud adoption by about 55%, largely because companies want to access data and tools from remote locations.

Other benefits of cloud adoption include:

  • Lowering IT costs.
  • Improving business agility.
  • Increasing collaboration.

You take a big risk when you store big data on-site without backing it up on the cloud.

Under-Using Analytics

When humans look at big data, they see a mess of information that doesn't make much sense.

It's impossible for the human brain to identify patterns from millions of data points. Analytical tools solve that issue by scouring data sets for patterns and inconsistencies.

Nearly all businesses understand that they need analytics to gain insights from big data.

Unfortunately, those same businesses under-use their analytical tools. That means they only get a portion of the potential benefits that big data can offer.

Ideally, you should use have big data analytics that helps you:

  • Streamline business processes to become more efficient and lower costs.
  • Identify customer preferences, pain points, and other factors you can use to personalize marketing.
  • Improve pricing strategies to win against competitors and retain customers.
  • Spot cyberthreat signs before they have an opportunity to cause serious problems.
  • Monitor your business's online reputation and improve branding.
  • Predict industry trends to stay ahead of the curve.

You may need to adopt multiple analytics tools to get the most from your big data.

Then again, you might not know that your current tools have additional features that will expand your insights.

It's best to talk to a big data analytics expert to determine whether you're missing opportunities.

Increasing your data and analytics costs by a small amount could lead to significant improvements within your business.

Collecting Data Without Oversight

For the most part, big data collection and storage happen automatically. Depending on your needs, you can back up data every hour or once per day.

Automation helps prevent human error from harming your data collection.

You still need someone to oversee your data collection strategies. Some businesses give that responsibility to one person, such as the CTO.

Other organizations give the responsibility to a board of people who can consider multiple perspectives and choose policies that fit their business needs.

Regardless of how you approach data oversight, you need someone in charge of studying big data trends, learning about emerging tools and features, and partnering with data professionals who can provide better services than in-house talent.

Big data and BI analytics are relatively new areas, so the technologies evolve quickly.

Without someone overseeing daily operations and in charge of updating policies, you will miss opportunities for making your business more competitive.

The CDC's current recommendations focus on public health data, but you can apply several of the guidelines to any industry.

They include:

  • Adopting policies that ensure the quality of data.
  • Collecting the minimal amount of personally identifiable information.
  • Respecting the privacy rights of individuals.
  • Minimizing the number of people who have access to data.

Perhaps most importantly, you need someone in charge who will act as a trustworthy steward for using bid data in responsible ways.

Not Prioritizing Data Security

More likely than not, any cloud service provider you use will encrypt your data. Don't assume that encryption solves all of your data security issues.

You can improve your data security by:

  • Anonymizing data to make re-identification considerably more difficult.
  • Data masking to separate confidential information from information that could help hackers identify people, accounts, etc.
  • Adopting real-time security compliance tools that monitor your data systems for unauthorized access and suspicious activities.
  • Performing regular security audits to ensure your policies meet current expectations.
  • Using multi-factor authentication to prevent unauthorized users from accessing data.
  • Embracing least privileged access that restricts data and application access only to those who need it.

Big data mistakes can put your business, clients, and partners in jeopardy. Improve your approach to big data usage and security by contacting Adservio.

Our team of experts can give you services and advice that make your big data application more effective than ever.

Published on
July 5, 2021

Industry insights you won’t delete. Delivered to your inbox weekly.

Other posts