7 Helpful Tips for Managing Big Data
University professors and statisticians are using data in a big way that has led to a new industry -- that of collecting and managing big data. Almost all businesses are contributing to big data, according to experts. Because the industry is fairly new, the way to manage big data hasn’t been spelled out completely.
If you are looking for ways to manage your data, this article might help, but first, let’s get the basic concept right.
What Is ‘Big Data’?
Before you can attempt to manage big data, you first have to know what the term means, said Greg Satell in Forbes Magazine. He said the term has moved to buzzword status quickly, which has gotten people talking about it. More people are enthusiastic and are making the investment in the crucial area. Yet, the hype has caused everything to be considered big data. People are confused about what big data encompasses.
Like I said in a previous article on this blog:
...Big Data is any data sets too large to process using conventional methods like an Excel spreadsheet, Powerpoint or text processors. Sometimes, it takes parallel software running on thousands of servers just to handle Big Data. Things like keyword research, social media marketing and trend searches all use Big Data applications, and if you use the Internet – of course you do – you’re already interacting with Big Data.
Satell quotes a book that argues big data are those things done on a large scale that can’t be completed on a small scale. This definition relates to studies that aren’t accurate because the sample is too small.
Determining the free throw percentage of a player is not statistically accurate unless you base it on numerous tries. By increasing the data we use, we can incorporate low-quality sources, but we are still accurate. This is the idea of using billions of data points to analyze something important.
Here are some smart tips for big data management:
1. Determine your goals.
For every study or event, you have to outline certain goals that you want to achieve. You have to ask yourself questions. You want to discuss with your team what they see as most important. The goals will determine what data you should collect and how to move forward.
Without setting clear goals and mapping out strategies towards achieving them, you're either going to collect the wrong data, or too little of the right data. And even if you were to collect the right amount of the right data, you'd not know what exactly to do with it. It just makes zero sense to expect to get to a destination you didn't know.
2. Secure your data.
You have to make sure that whatever container holds your data is accessible and secure. You don’t want to lose your data. You can’t analyze what you don’t have. Ensure you implement proper firewall security, spam filtering, malware scanning and permission control for team members.
Recently, I attended a webinar by Robert Carter, CEO of Your Company Formations and he shared his experience with the entrepreneurs they work with. He said many businessowners collect data from users' interactions with their sites and products but don't take any or enough precautions and measures to secure the data. This has cost some businesses their clients' trust, crashed the businesses of some others, and even sent some bankrupt with heavy fines in damages.
"Securing your data appears like an obvious point but too many businesses and organizations observe the advise in the breach," he concluded. So don't be one of them.
3. Protect the data
Aside human intruders and artificial threats to your data, some natural elements could also corrupt your data or make you lose them totally.
Often, people forget that heat, humidity and extreme cold can harm data. These problems can lead to system failure which causes downtime and frustration. You want to watch for these environmental situations, and take actions to stop your data loss before it happens. Don't be sorry when you can avoid it.
4. Follow audit regulations
Even though many data managers are on the go, they still must maintain the right components in case of an audit. Whether you're managing customer's payment data, credit score (or cibil score) data or even seemingly mundane data like anonymous details of site users, you have to manage your assets correctly.
This ensures you stay safe from liability and continue to earn cutomers' and users' trust.
5. Data need to talk to each other
Make sure you use software that integrates many solutions. The last thing you need is for you to have problems caused by applications not being able to communicate with your data or vice versa.
You should make good use of cloud storage, remote database administrator and other data management tools to ensure seamless synchronization of your data sets, especially where more than one of your team members do access or work on them simultaneously.
6. Know what data to capture
When you are the manager of big data, you have to understand what data are the best for a particular situation. Therefore, you have to know which data to collect and when to do it.
This goes back to the basis: Knowing your objectives clearly and how to achieve them with the right data.
7. Adapt to changes
Software and data are changing almost daily. New tools and products hit the market daily making the previous gamechanging ones seem outdated. For instance, if you sell toothbrush and you already know a lot about your customers' taste after having collected data about their demographics and interests over a period of six months, you'll need to change your sales strategy if the need and taste of your customers start showing a strong preference for electric tootbrush over the manual one. You'll also need to change how you collect data about their interests. Refusing to adapt in that situation is a recipe for failure.
You have to be flexible to adapt to new ways of managing your data and to changes in your data. That's how to stay relevant in your industry and truly reap the benefits of big data.
Keeping these tips in mind will help you handle big data in an easy manner.
Have some tips about managing big data? You’re welcome to leave a comment below
Abdullahi is a writer and Big Data enthusiast. He has two published books and loves exploring all things analytics. When he's not writing or eating some data research, he's hanging out with friends or planning how to create a monumental dent in the universe. Follow him on Twitter: @Oxygenmat