Data is an essential part of most companies; however, in the last five years, data collection has evolved. Previously, companies would be required to collect their data daily and load it into a database. Today, click-steam data collection is more common. This method of data collection has led to an explosion of data sources and the creation of what we call “big data.”
The existence and complexity of big data has led to a need to be able to contain and process such massive quantities of information. In order to accomplish this monumental task, companies must develop a big data plan for managing, storing and using the flood of information.
Here are four common big data strategies business implement to do just that:
Strategy A: Use Performance Management for Organization
Performance management (PM) creates a way to understand the big data that naturally flows into a medium or large-sized company. PM uses both a series of pre-determined queries (to organize the data sets) and multidimensional analysis (a process of grouping big data into categories including dimensions and measurements). Moreover, PM systems can hold years of a company’s data, which can then be used for any number of reports and graphs to analyze business trends.
Strategy B: Make Data Exploration Work for You
Data exploration uses experimentation (specifically of website components to achieve high traffic conversion rates) and statistical data to answer questions about the health of a company. In terms of experimentation, companies can use data exploration to determine which website mockup will perform best, which content will be most useful to users, which landing pages and/or designs will lead to clicks, etc.
Strategy C: Analyze the Impact of Social Media
Social analytics is becoming increasingly important to companies as an increasing amount of data is being drawn from social media platforms. For example, a good deal of data comes from reviews via Facebook, Yelp and Twitter. Recently there has been an influx of mobile apps, like Foursquare, that are also generating a lot of data. Measuring the engagement of customers using these social platforms is a great way to stay ahead of the competition who may be ignoring this crucial data source.
Strategy D: Decision Science
Like social analytics, decision science takes non-transactional data and experiments with it to enhance a company’s decision-making. Often this type of data comes from consumer ideas, as well as product reviews. Decision science data, unlike social analytics, is used to test company hypotheses.
As the Ivey Business Journal states, managers don’t have to just pick one big data strategy, rather “the most effective companies leveraging big data today are combining strategies.” Implementing an effective big data strategy is about finding the best combination of data management practices to fit your individual company’s needs.
Here at Ad Victoriam Solutions, our big data and data intelligence consultants can not only help you map out a data management plan, we also provide the solutions and help you need to get the job done. We’re with you from start to finish!
If you require a strategy for translating data into useful solutions for your business, browse our blog or contact us and we’ll devise a way to enhance your company and solve all of your cloud-computing needs.