We create 2.5 quintillion bytes of data each day and 90 percent of the data in the entire world has been created in the past two years. Those numbers are truly staggering but when you consider all the data outputs in today’s world, the amount isn’t as surprising.
After all, we’re in the age of connectedness—we have sensors that we wear, devices that have the ability to report data back to us and companies are generating data at an incredible rate. People send nearly 20 billion text messages per day and that’s only one-third of the activity that some popular messaging apps see.
But big data is more than the collection of a lot of bits and bytes. Once analyzed, it provides valuable insight into behaviors and interactions. Big data allows you to discover powerful patterns and you can use that intelligence to streamline operations, personalize customer experience and plan strategic growth. Such perception enables you to stay ahead of competitors and remain a leader, and it is truly necessary for a successful digital experience in the modern world.
However, some organizations are finding that more data is not always better data. There are challenges to overcome when you’re faced with so much information. Consider the following data management strategies to find the approach that will set you up for greater success.
The Collector Approach with the DIY Analyst
There’s a lot of data out there that your company may have access to, and some companies choose to use a collector approach to gather all that they can. The central focus of this strategy is to collect now and deal with analysis later. At the time, all of the data seems valuable, and to not obtain or store available data feels equivalent to letting valuable worth go. After all, the right data can be a major asset.
However, be aware that hoarding a giant pile of data is not always useful and may even cloud the integrity of data that is important. While you may assume you’re gaining value by mere quantity—more often than not, companies end up with an unwieldy, disorganized pile of data that creates inefficiency and causes risk. Big data means bigger responsibility. You have to not only think about storage costs, integration and security, but you must also find a way to navigate and analyze it effectively.
So much data truly requires a DIY-minded analyst to sort through all of the information to find what is important and relevant. However, the process may waste your employees’ time. For example, if one of your analysts is looking into ad impressions from multiple databases and locations, his or her ability to find insight may be hindered by of the sheer amount of information that exists.
Querying constructive views of data for a specific project may take longer than it should because the software will become overburdened—what should only take less than a minute may end up taking 5 minutes or more. If 10 queries need to run each day, that’s wasting nearly an hour of your analyst’s time. If you have multiple analysts all looking to run complicated queries, then even more employees will face similar delays. To combat this data overload, consider using a data management strategy that is more thoughtful and aware.
The Planner with the Solution-Ready Approach
Take the planner approach to data management to avoid dealing with more data than you can handle. Instead of collecting information simply because you can acquire it, collect data because you already have an idea of what you plan to do with it.
Set an intention and go from there. Doing so will allow you to avoid the unnecessary collection, storage costs and management burden of data that doesn’t have a place in your business function or project level. If there is data that you decide you need later on, you can always go capture it then. Be thoughtful and judicious about what you need to collect and then aim for a minimalistic approach in gathering that data. Look at the following data cycle to see how the process may work.
The Data Cycle for Success
1. Set intentions: What topics do you plan to explore and what questions do you have? Once those are determined, take a minimalistic approach to gather the data you need.
2. Store carefully: Warehouse your data securely while balancing the need for ease of access.
3. Integrate: Make sure the data is easy to navigate. Unify disparate databases and data set locations so that analysts can easily research information.
4. Translate and analyze: Analyze the data to discover patterns and trends. Then seek actionable insights.
Invest in this planner approach to make research easier for your analysts and it will pay off in success. Instead of the collector mindset of it’s “not my job to analyze”, aim to make the data more accessible and solution-ready. By minimizing what you truly need before adding to your data collection, you will also improve efficiency.
You do not necessarily need to have set expectations at the first step of the cycle—but you do need to have intentions. Business intelligence may yield surprising results that you did not previously expect. By ensuring the data is easily accessed, you may find that one department’s success leads to insight in another department.
For example, an analyst may find that a higher site arrival rate correlates with an ad’s impressions at a certain time of day. This may cause the advertising team to consider the use of alternate ads based on whether it’s morning, afternoon or evening. You never know what direction analysis will bring you if data is easy to navigate.
This data management strategy offers a more business-minded approach. While a collector or academic mindset may be to gather data in order to learn something new or discover interesting insight, the business approach with a narrow scope allows for ease of access and interpretation of data. This will lead to greater insight without complicated queries or tedious, error-prone work.
Harnessing big data can have a tremendous impact on the growth and success of your business if done right. Avoid the pitfalls and inefficiencies of excess data by only collecting the information you need.
If you’re following big data through its cycle, you can see worthwhile results. As long as you set intentions, seek actionable insights and have a planner approach over a collector approach, there may be a valuable return. After all, data is doubling in size every two years. Use the information to your advantage—just be smart about it.
(About the author: Seth Birnbaum is the chief executive officer and co-founder of EverQuote, the largest online auto insurance marketplace in the U.S.)
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