UPDATED 14:00 EDT / MARCH 19 2018

BIG DATA

Intel works across tech ecosystem to democratize data science tools, expand diversity

One of the challenges confronting the data science industry is finding ways to make sophisticated analytics tools easier to use across cloud and data center platforms within multiple industries. The data layout matters, and Intel Corp. has issued the latest version of its Math Kernel Library in an effort to help developers leverage instruction sets and improve hardware or software performance.

The library is yet another step Intel has taken to expand the availability of tools and resources as it leverages the power of bringing the big data ecosystem and data sciences solutions together into a coherent whole. On the hardware side, Intel has introduced new tools to streamline software development on field programmable gate arrays. These powerful and versatile chips can process data at the edge and provide artificial intelligence support.

“We’re working with the top seven cloud service providers, both in the U.S. and in China, to democratize not only our hardware, but also our libraries and tools,” said Ziya Ma (pictured), vice president of the Software and Services Group at Intel. “Our goal is to provide all of the necessary solutions so that at the end, our customers can create the application, the solution that they really need to address their biggest pain points.”

Ma spoke with George Gilbert (@ggilbert41) and Lisa Martin (@LuccaZara), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. In a separate appearance on theCUBE, Ma spoke with Martin at the Global Women in Data Science event held in Stanford, California. They discussed various projects that Intel is pursuing in the data science space, the company’s continued focus on a number of industry sectors, career advice for entering the data science field, and initiatives to expand diversity in the technology world.

This week, theCUBE spotlights Ziya Ma in our Women in Tech feature.

Graph project for deep learning

One key project that could go a long way toward democratizing tools is Intel’s Nervana Graph project. The company’s researchers are working on a hardware-independent representation for deep learning that can be executed across platforms with minimal effort.

“That will encapsulate the hardware integration details and present a consistent API for developers to work with,” said Ma, who expressed hope that the project will push more tools into the mainstream.

Intel has also been working on various data science applications for a wide range of industries. The company has engaged with customers across a broad cross-section of the enterprise ecosystem to better understand how data science can make a difference in the delivery of services or improved efficiency.

“We’re working with the financial services industry; we’re working with the manufacturing sector and customers from the medical field and online retailers, trying to help them create data science and analytic solutions,” Ma said. “We’re seeing very good progress in this area.”

Watch the complete video interview with Ma from the BigData SV event:

Intel’s work with the University of California San Francisco’s Center for Digital Health Innovation offers an example of how the firm is collaborating in the analytics space. The company has been focused on the deployment of deep learning and machine-driven workflows to support the clinical environment and provide positive outcomes for patients.

One data science application involves finding ways to improve the assessment of magnetic resonance imaging for patients with damaged cartilage often caused by degenerative disease, such as osteoarthritis. “We helped the medical center to automate the diagnosis and grading of meniscus [joint cartilage] lesions,” Ma said. “The result is much more accurate, consistent and timely because you don’t have to wait for the availability of a radiologist to read all of the 3D or MRI images. That can all be done by machines.”

Filling the skills gap

A report jointly issued by IBM and the Business-Higher Education Forum found that openings in the analytics and data science fields will increase 15 percent by 2020. Interestingly, the research showed that hiring need for traditional data scientists is expected to be only two percent of the demand while a third of the openings will comprise other categories, such as marketing managers trained in data analysis.

With her experience in managing Intel’s Big Data Software Technologies organization, Ma is often approached for advice on how to build a career in the data science field. In addition to marketing, there is also demand for data science skills across a wide range of professions, including sales, data engineering, virtualization, statistical research and artificial intelligence, according to Ma.

“Data science appears to have a high bar today, and it may be too significant a job to move from where you are to the data science field,” Ma said. “Assess your skill set gap, and then work to close that gap. You may want to move to an adjacent field first.”

Watch the complete video interview with Ma from the Global Women in Data Science event:

Improving tech diversity

Closing the skills gap is one thing. Finding women to fill data science openings is another matter entirely. When Intel needed to fill positions in its big data organization, Ma was disappointed in the diverse representation of applicants.

“There were very few women in the candidate pool,” said Ma who reached out to other tech companies to discuss the dilemma. “It turned out everyone had the same problem.”

An outgrowth of the hiring challenge was the formation of the Women in Big Data Forum, designed to strengthen diversity in the field. The initiative now has 2,000 members globally with chapters established on both U.S. coasts, Europe and Asia.

“We work with our industry partners to offer free training classes,” Ma said. “We also started reaching out to universities to build the pipeline, to motivate female students to get passionate about analytics and big data.”

Three years ago, Intel announced the Capital Diversity Initiative, a $125-million project to foster business opportunities for minority and female entrepreneurs. In 2016, Intel Capital expanded the fund’s focus to include military veterans, people with disabilities, and members of the LGBTQ community.

The company’s moves are designed to more fully address the issue of representation inside the technology world. Paraphrasing her boss, Intel Chief Executive Officer Brian Krzanich, Ma said, “If we want tech to define the future, we must be representative of that future.”

Be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event and the WiDS event.

Photo: SiliconANGLE

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