Best Practices for Data You Can’t Ignore: Get More from Your Data

best practices for data

To say that data has become one of the most revolutionary forces in modern business and is only like to grow more important as time goes by is an understatement. Businesses find that using data the right way helps make their business more secure, can help them understand their customers and how better to reach them, and can improve internal processes and workflows across the board. If you use data in your business, or even more critically if you aren’t using data to provide insights into best management practices, then you need to know how to use it well. For that reason, let’s look at some best practices for data that you need to know.

data analysis
Image courtesy of Markus Spiske

Security is your number one concern

You only need to look at the news following some of the major data breaches of the 2010s to see just how important data security is. If you suffer a data breach and fail to protect customer data, for instance, you’re likely to suffer major fines and loss of consumer confidence that result in reduced profitability. In fact, most businesses experiencing a major data breach close within two years after its occurrence.

Hence protecting your data is a serious consideration and you must take multiple steps to protect your data, including making sure it’s in a controlled and secured server, encrypting it, and teaching your employees the importance of digital security practices, including making sure that they don’t leave terminals with access to data logged in and unprotected and know how to recognize and thwart efforts at phishing.

Hire a team that can make good use of your data

Analyzing and interpreting data to provide meaningful insights requires specific training and expertise, especially if you’re using Big Data collected across a wide range of sources.

Hire people with expertise in data analysis who can read, gather insights from, and offer advice based on the data that’s being collected. As such, data analysts need training in their field, as well as the attention to detail and a strategic mindset to understand the data they’re analyzing. Specialized skills in software products such as R, SQL, and Python require some coding skills. Analysts also need a creative mind and an understanding of business perspectives to apply data and guide analysis to questions and problems that determine future strategies and tactics.

If you have people with perspectives in business practices, but not the data analysis skills to go with them, you could always look into data analyst training courses.

Ensure you’re scaling your tools to your needs

Initially, you may not need more than a hard drive to contain all the data your business wishes to retain. However, as your data collection and insight gathering needs grow, so too will your need to house and manage more data. Making the move from the most basic of storage to on-premises servers or Cloud storage is one step. Here’ AWS, an Amazon product, provides secure data storage at a very reasonable cost that makes them the preferred choice of many companies in both the Fortune 500 and SMEs.

You also need to look at how you’re managing the data through databases, such as an Oracle forms migration. Ensuring that your data remains accessible, organized, and responsive to your needs is key. The more data you collect and the more complex it is, the more likely that more basic, middleware database systems are to struggle with it.

best practices for data Image courtesy of Lucas

Know that not all data is the same

Another best practice for data is an awareness that collecting and storing data comes at a cost; the more data you have the more costly. Too much data might also make analysis less effective as analysts try to glean insights from data that has nothing to do with management practices or reflect uncontrollables. Thus, some data is more valuable than others.

It’s important that your team focuses on gaining high-value data while knowing what to expunge from the database or never collect in the first place. The easiest data to cast aside is data that’s too old. You need to also look for duplicate data, as they can skew the results of any analysis, making it seem like certain results are more common than they actually are, for instance. Teach your data analysis team the importance of valuing their data is crucial to making accurate insights.

Ensure you have decent access controls in place

To make the best use of your data, you must ensure the right people have access to it whenever they need it while restricting access to only those who have a legitimate need for the data. This is a two-step best practice for data: controlling access while providing improved access to others

Your data analysts won’t be able to make a complete picture if certain datasets are cut off from them, for instance. Allowing access to folks who don’t need access means open you business up to potential hacking or the bad acts of employees. As such, you need to develop access controls that balance the fine line between accessibility and security.

It’s best to manage access to data on an individual level, but you should also consider giving administrative privileges to whoever is at the head of the data analysis team. They are more likely to know the needs of the team that reports to them and can help you avoid the restrictive nature of blanket policies.

Well designed tools help apply access controls. For instance, Google Analytics segments data such that the administrator can allow access to needed data to users without giving them access to the entire dataset collected by the tool. Product managers gain access to data related to their own product line without seeing sensitive data about other product lines controlled by other managers unless the organization determines such assess benefits to organization, as a whole.

Make use of visualizations when presenting data

The ability to communicate well is essential for data analysts. They have to be able to talk to managers and leadership staff about the insights they have found in the data without getting too bogged down by confusing figures and jargon. You can make it easier for them by using data visualizations, after all, a picture paints a thousand words..

A range of tools exist to help your team translate datasets into a range of visuals, including graphs, charts, and more, that make it much easier to show and communicate trends and drive home insights resulting from the analyst’s work. As such, analysts find their job to convince managers, leaders, and others of what they’ve gleaned from the data easier with effective and appropriate visualizations.

best practices for data

Have a fully effective data recovery plan

As much money and effort as you may invest in security and good data storage, you can’t protect it from every single risk. Whether due to a breach or an accident, you may lose access to your data or you may lose it completely. Even if it’s not stolen by someone else, losing that data can be hugely detrimental when it comes to sales, customer relationship management, marketing, and more. Having a data recovery strategy is essential. This can include having a backup copy, such as having a hard drive as well as a Cloud-based solution working at the same time.

Data is becoming increasingly important to the future of business. However, your ability to use it to its greatest potential lies in how able you are to follow the best practice tips above. It’s not worth taking any risks when it comes to data.

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