8 reasons you'll do big data this year

Over the past 12 months, I’ve been digging in the data trenches. OK, mostly I’ve been sitting next to the smarter people digging through the trenches and oversimplifying what they were doing in reports to management.

Very few IT projects are truly unique — and the ones that sound unique often fall into relatively predictable buckets. Lucky for you, I’ve decided to come up for air and share the top eight types of projects I’ve seen over the past 12 months.

1. Exploring the life of a deal

Companies that do e-commerce take for granted that you can hook up a few tools and know the close rate of users coming to the website, from sales to payment. But many companies deal with a lot more data sets than Web-to-close. Mainly those data sets originate from distributors and resellers.

Each distributor or reseller presents a different data set in a different format. Sure, fundamentally, this is a core ETL/data consolidation project with BI/visualization on the front end. But for many companies, truly understanding the life of the deal (from inception to close and ongoing) is more difficult than you think. You need to combine a lot of CRM, Web analytics, and finance to say, “Yes, PPC yielded closings, but 40 percent of those customers defaulted on the first bill, so …” 

Adobe adds data-science muscle to its cloud services

Finding insights in an ocean of data has become one of today’s most pressing business challenges, and software vendors are rushing to help. The latest is Adobe, which has added a host of algorithms in its cloud services to help brands uncover patterns and put them to work.

Adobe’s Creative, Document and Marketing Cloud services already use data science to help brands hone their message to customers, and the algorithms announced Wednesday add more capabilities.

In the Marketing Cloud, for instance, a new auto-allocate capability billed as a “content traffic cop” helps marketers identify the best offers, messaging and creative materials for engaging with customers. An online retailer could use it to determine that a particular promotional video is driving the most purchases, and automatically push that video to more online visitors even as it tests other content.

Users of Adobe’s Campaign tool, meanwhile, can now test predictive subject lines through a new beta program. The technology suggests which email subject line will yield the best results from a marketing campaign.

Huawei Prepares for Robot Overlords and Communication with the Dead

(Bloomberg) — Chinese technology giant Huawei is preparing for a world where people live forever, dead relatives linger on in computers and robots try to kill humans.

Huawei is best known as one of the world’s largest producers of broadband network equipment and smartphones. But Kevin Ho, president of its handset product line, told the CES Asia conference in Shanghai on Wednesday the company used science fiction movies like “The Matrix” to envision future trends and new business ideas.

“Hunger, poverty, disease or even death may not be a problem by 2035, or 25 years from now,” he said. “In the future you may be able to purchase computing capacity to serve as a surrogate, to pass the baton from the physical world to the digital world.”

Salesforce IoT Cloud Uses AWS to Support its "Uncontrolled Exponential Growth"

Amazon Web Services (AWS) has added a potentially huge infrastructure client in Salesforce’s Internet of Things (IoT) Cloud, The Wall Street Journal reported on Tuesday. Salesforce’s IoT Cloud, which was announced in September, utilizes the Salesforce Thunder processing engine, and partnerships with ARM, Etherios, Informatica, PTC ThingWorx, and Xively LogMeln.

Salesforce IoT Cloud executive vice president Adam Bosworth told the WSJ that his company chose to use AWS’ infrastructure because the “uncontrolled exponential growth” of the service meant it “had to have the safety valve of a public cloud or public clouds to do what we were doing.” He also said that the Salesforce IoT Cloud is designed to run on any public cloud, and on its own servers, and he anticipates a mix to satisfy customers who want to keep data in Salesforce’s own data centers.

Read more: Salesforce: Most Successful Marketers Plan to Increase Technology Spend Over Next Two Years

Rackspace CEO: Q1 2016 Growth Driven by Managed Cloud Services Demand

Rackspace is the latest hosting company to post quarterly earnings, reporting adjusted earnings of 34 cents per share on Monday, far above the 22 cents predicted by Wall Street analysts. For the first quarter of 2016 Rackspace posted a net income of $49 million, up 77.5 percent from Q1 2015.

Net revenue was up 7.9 percent from a year ago to $518 million, roughly meeting analysts expectations, but adjusted for currency factors and the sale of cloud storage provider Jungle Disk, it grew by 9.9 percent, driving GAAP EPS of 37 cents. The company’s adjusted EBITDA grew 11.7 percent over Q1 2015 to $179 million, and its adjusted free cash flow and return on capital were up from a year ago.

“We’ve continued to build market power behind our managed cloud strategy,” said Taylor Rhodes, president and CEO of Rackspace. “Demand for Rackspace’s managed services for AWS, the Microsoft cloud, and our OpenStack private cloud is scaling rapidly. Collectively, we now deliver expertise and support for more than 400 customers on these cloud platforms, including some of the world’s largest companies and leading brands such as Digitas. While we are experiencing hyper-growth in these new offers, we also continued to reduce our capital intensity and boost our free cash flow.”

RightScale Cuts Own Cloud Costs by Switching to Docker

Brought to you by Data Center Knowledge

Less than two months ago, the engineering team behind the cloud management platform RightScale kicked off a project to rethink the entire infrastructure its services run on. They decided to package as much of its backend as possible in Docker containers, the method of deploying software whose popularity spiked over the last couple of years, becoming one of the most talked about technology shifts in IT.

It took the team seven weeks to complete most of the project, and Tim Miller, RightScale’s VP of engineering, declared the project a success in a blog post Tuesday, saying they achieved both goals they had set out to achieve: reduced cost and accelerated development.

Is your data safe when it's at rest? MarkLogic 9 aims to make sure it is

The database landscape is much more diverse than it once was, thanks in large part to big data, and on Tuesday, one of today’s newer contenders unveiled an upcoming release featuring a major boost in security.

Version 9 of MarkLogic’s namesake NoSQL database will be available at the end of this year, and one of its key new features is the inclusion of Cryptsoft’s KMIP (Key Management Interoperability Protocol) technology.

MarkLogic has placed its bets on companies’ need to integrate data from dispersed enterprise silos — a task that has often required the use of so-called ETL tools to extract, transform and load data into a traditional relational database. Aiming to offer an alternative approach, MarkLogic’s technology combines the flexibility, scalability, and agility of NoSQL with enterprise-hardened features like government-grade security and high availability, it says.

Now coming up in the next generation of the software will be a variety of improvements in data integration, manageability and security, the company says, but certainly most notable among them is the addition of Cryptsoft’s KMIP.

Review: 6 machine learning clouds

What we call machine learning can take many forms. The purest form offers the analyst a set of data exploration tools, a choice of ML models, robust solution algorithms, and a way to use the solutions for predictions. The Amazon, Microsoft, Databricks, Google, and IBM clouds all offer prediction APIs that give the analyst various amounts of control. HPE Haven OnDemand offers a limited prediction API for binary classification problems.

Not every machine learning problem has to be solved from scratch, however. Some problems can be trained on a sufficiently large sample to be more widely applicable. For example, speech-to-text, text-to-speech, text analytics, and face recognition are problems for which “canned” solutions often work. Not surprising, a number of machine learning cloud providers offer these capabilities through an API, allowing developers to incorporate them in their applications.

Source: InfoWorld Big Data

Microsoft to Launch Cloud Data Centers in Korea

Brought to you by Data Center Knowledge

Microsoft announced plans to build cloud data centers in South Korea as the race to expand global reach of their cloud infrastructure among the largest public cloud providers, including Amazon and Google, continues.

Ecommerce Software Platform BigCommerce Raises Million

BigCommerce announced on Tuesday that it has received $30 million in a Series E funding round led by GGV Capital. All of BigCommerce’s existing investors participated in the round, including General Catalyst, Revolution Growth, SoftBank Capital, Tenaya, Split Rock, Telstra Ventures, and American Express Ventures.

According to research by Morgan Stanley, the addressable market for ecommerce software platforms is now over $10 billion annually, with 46 million merchants globally and 10 million in Western markets. Gartner counts the cloud ecommerce enablement software and services market at $7.7 billion in 2015, and expects it to hit $10 billion in 2018, BigCommerce said.

“BigCommerce is benefitting from the retail industry shifting online, with every small, mid-sized and large merchant in the world seeking to gain a piece of the $1 trillion ecommerce market,” said Brent Bellm, CEO of BigCommerce. “This new financing follows on the successful launch of several new products, our partnerships with major players in ecommerce like eBay and Square, and our successful expansion into the midmarket.”