Today’s companies are generating — and making use of — data at unprecedented rates. But there are many companies who are faced with growing amounts of data yet aren’t making the best use of the data they’re gleaning from their customers and even from public data sources, whether because they lack adequate Big Data Analytics tools and techniques, are looking at the wrong data sets, or possibly asking the wrong questions.
More importantly, Big Data Analytics in today’s world means hiring the right team of data scientists, analysts, and other professionals who know their way around a data set and can carry out statistical analysis with ease. Getting the right team in place is just one facet of getting the most value from your data.
To find out what companies who want to improve Big Data Analysis should be focused on, we asked a panel of data experts, data scientists, and business intelligence professionals to answer the following question:
“What’s the #1 thing or technique companies can leverage today to double the effectiveness of their Big Data Analysis efforts?”
Find out what our experts had to say below.
Apryl DeLancey is the President and CEO of Social Age Media. Based in Los Angeles, she’s not just a data scientist; she’s a data enthusiast.
“The number one thing that companies can do today to double the effectiveness of their Big Data Analysis efforts is…”
To assure they have the right team in place. This means not only your expert programmers and statisticians, but making sure one or more of them can also gather deep insights from the data and make actionable recommendations. In other words, someone that understands not only the numbers, but the strategic implications.
Josh Jennings is the Chief Information Officer for a hedge fund and also a co-founder and CEO of a data science focused startup company called Financial Intellect.
“The primary thing companies can do to double the effectiveness of their Big Data Analysis efforts is to…”
Engage an outside specialist. Often times it requires a fresh look from an outsider to come up with innovative ways to use the data. Employees and people that use the data daily may become myopic and suffer from tunnel vision. The problem is that there are a shortage of qualified people, and the qualified people are usually expensive. Firms should weigh the cost benefit of engaging a consultant and negotiate a fee based on performance.
Mikko Jarva is the CTO, Intelligent Data at Comptel Corporation. Based out of the company’s Kuala Lumpur office, he started his career with Comptel in 2000 as a trainer and product specialist. Since then, he has held positions in product marketing, sales, technical sales, and business development before entering his current position at the company in 2015.
“In order to improve Big Data Analysis, companies should remember…”
Apps, social media, cloud, and the sharing economy are all elevating customer experience expectations. Operators are no longer just dealing with traditional mobile data, but also have to consider connected devices, which are changing the way that businesses need to react to expectations.
Operators’ strategies need to, therefore, be based on granular, dynamic and in-the-moment assessments of buyers’ contextual needs. For instance, the whole Big Data paradigm needs to shift to an approach in which data is refined and analyzed simultaneously and actions should be taken automatically. We are past the era of Big Data – now, it’s time for Intelligent, Fast Data.
This is real-time, enriched operational data, which can be immediately utilized for instant decision-making and action-triggering. Data has the most value in the moment it is captured, when intelligence can be immediately extracted from it.
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