Big Data In Use

“You Need to Fall in Love with Data” – Interview with Vojta Rocek, Trologic

This blog post is part of the Big Data Week Speaker interviews series. Vojta shares his thoughts about the importance of changing  mentalities when it comes to data-driven businesses, and about a new culture of decision making. Why is it important for businesses in your industry to be more data driven nowadays? In today’s increasingly complex and dynamic business world, you can’t afford to make decisions based solely on intuition. You need to understand what works and how it works. You need to fall in love with your business data and instill this love to everyone in the company. What are the main challenges a company encounters when trying to leverage their data? People’s mentalities. Around 70 % of the staff usually […] Continue Reading

“Self-Service Data” Approach, the Future of Data Analysis – Interview with Arturo Canales, Telefónica

This blog post is part of the Big Data Week Speaker interviews series.  Arturo talks about the challenges and the impact of big data in the telco industry, also offering a sneak peek into his talk at the “Big Data in Use” Conference | Big Data Week 2016. Why is it important for businesses in your industry to be more data driven nowadays? In telco, as almost in any other industry, data is becoming one of the most valuable assets for both companies and individuals. Making a wrong decision can mean a huge difference or impact. This is why decision makers need to be able to access any insight that can be derived by looking at the company data, and understand what is really going on, so they can really […] Continue Reading

“Big Data Innovation Happens at a Tremendous Pace and There Is No Prize for Second Place” – Interview with Harry Powell, Barclays

This blog post is part of the Big Data Week Speaker interviews series.  Harry shares his thoughts on Fintech challenges, the impact of big data in the Finance field, also offering a sneak peek into his talk at  “Big Data in Use” Conference | Big Data Week 2016. Why is it important for businesses in your industry to be more data driven nowadays? Finance has always been data-rich and data-driven but the big data technologies have enabled us to use data to deliver an experience and product at a customer level whereas before data was only used to report aggregated information to managers. And if we don’t do it there is a legion of Fintech challengers looking to do it instead. […] Continue Reading

Hadoop & Spark are Dominating Big Data, But the Market Demands Even More

According to industry insider and InfoWorld columnist Andy Oliver, what you need to know about Hadoop is that it is no longer Hadoop. At least, it isn’t the Hadoop that everyone once knew and may or may not have loved. Hadoop’s co-creator Doug Cutting believes that the changes are a direct result of the open source roots of Hadoop and related projects, most notably Spark. Together, Hadoop and Spark are dominating the big data marketplace, with Hadoop commanding half of big data’s $100 billion annual market value, and Spark surpassing MapReduce in terms of popularity (at least among those searching for big data products on Google). While Hadoop is the go-to big data framework and Spark reigns supreme when it […] Continue Reading

What the Machine Learning Element of Big Data Has to Offer the Retail Industry

What is machine learning? Machine learning (often shortened within the industry as ML) is a kind of artificial intelligence (AI), which is an offshoot of big data. AI, and by extension, ML, utilize big data in a different way than typical analysis. These practices are capable of taking in data, building assumptions based on the data, testing hypotheses about those assumptions, and drawing conclusions from the results. Though not nearly as complex and sophisticated as human learning, AI and ML can do rudimentary logic by themselves. Yes, it sounds a little creepy (and potentially even 2001 Space Odyessy-ish), but there are numerous practical uses for AI and ML. What can ML do for retailers?

Want to Be Successful with the IoT? Learn to Forge Smart Partnerships

Currently, there are roughly 23 billion connected devices on earth. By next year, that number will jump past 28 billion. By 2020, we will be contending with some 50-odd million connected devices. As those devices accumulate, the amount of data escalates, as well, doubling in size about every two years. By the year 2020, there will be 5,200 gigabytes of data for every person on the planet. This will account for an additional 40 zettabytes, which is about 57 times the number of grains of sand on all of the beaches around the globe put together. If you’re struggling to keep a few dozen or a few hundred users connected with reliable speed, performance, and security, imagine what it will […] Continue Reading

Do you know how safe your apps are?

Arxan Technologies, the company specialized in software security and mobile application protection has released its 5th annual State of Application Security Report. This report takes an in-depth look into the security of some of the most popular mobile health and mobile finance applications available today. The company surveyed 126 popular mobile health and finance apps from the US, UK, Japan, and Germany.

Ready for a Swim? How to Tell When You’re Ready for a Data Lake (or If There’s a Better Solution)

As most organizational data sets grow beyond the capabilities of the traditional data warehouse, a lot of businesses are taking a look at the option of building a data warehouse. But scanning the tech news headlines and IT blogs, you’ll find two camps: the one saying that the data lake is the salvation of your data architecture and data plans, and the camp that maintains a data lake is nothing but a data swamp — the place where good data goes to die without a decent burial.

4 New Big Data Security Worries

The past couple of years haven’t been easy ones for cyber security specialists, especially those charged with protecting the growing reservoirs of Big Data. The headlines featured more stories about data breaches than about most any other aspect of Big Data and related technologies — even though that time period marked some impressive improvements in terms of open source software, database technology, and the growing importance of the data scientist.

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