The Brandeis GPS blog

Insights on online learning, tips for finding balance, and news and updates from Brandeis GPS

Tag: enterprise data

Learn information technology management online at Brandeis

Did you know that Brandeis GPS offers courses for professional development? Enroll in an online course this fall and network with new colleagues in a 10-week, seminar-style online classroom capped at 20 students. Registration is now open and we’re celebrating by profiling our favorite fall courses.

Get an introduction to the “nuts and bolts” that span all areas of information technology. With this 10-week, graduate-level course, you’ll learn enough foundational information about each key area to assess and evaluate when and how each technology should be appropriately deployed to solve organizational challenges. Topics include:

  • An overview of the history of information technology
  • Telecommunications and networking
  • Data and transactional databases/enterprise systems (ERP)
  • Data warehousing and business intelligence
  • E-commerce and B2B systems
  • Security and compliance

Capture-2

Fall courses run Sept. 14-Nov. 22. Whether you’re looking to complete a full degree or advance your career through professional development, this course is designed to equip you with the necessary skills for making an impact in any industry or organization.

How it works:
Take a part-time, online course this fall without enrolling in one of our graduate programs. If you like what you learn and want to continue your education, you can apply your credits from this fall toward a future degree. Questions? Contact our enrollment team at gps@brandeis.edu or 781-736-8787 or fill out our first-time registration form and we’ll be in touch.

How Companies Can Use Big Data to Make Better Decisions

By:  – Associate Editor, BostInno

Big Data has swiftly earned a lasting place in our lexicon, because its potential is real and impact undeniable. Companies can collectively scoff and brush big data off as just another trend, but that decision could lead to worse decisions down the road.

how-predictive-analytics-can-make-money-for-social-networks-46ce73d0c0“Every era has a bold new innovation that emerges as a defining advantage for those who get out ahead of the curve,” said Ali Riaz, CEO of enterprise software company Attivio, referencing the industrial revolution and, later, the information age. Giants of industry who took advantage of new machinery or market leaders who learned to leverage relational databases have historically had the upperhand.

“Today’s advantage — the new currency, if you will — is big data,” Riaz added. “Companies that don’t get ahead of this tsunami by using big data to their advantage will be crushed by it.”

Yet, this deluge of data isn’t new, it’s just been given a catchy two-word title.

When asked to define big data, Ely Kahn, co-founder and VP of business development for big data start-up Sqrrl, described it as massive amounts — tera- and petabytes’ worth — of unstructured and semi-structured data “organizations have historically been unable to analyze because it was too expensive or difficult.” With technologies like Hadoop and NoSQL databases surfacing, however, Kahn claimed those same organizations can now make sense of this type of data “cost effectively.”

To Marilyn Matz, CEO of fellow big data startup Paradigm4, the revolution goes beyond just high volumes of information, though.

“It is about integrating and analyzing data collected from new sources,” Matz said. “A central capability this enables is hyper-personalization and micro-targeting — including recommendation engines, location-based services and offers, personalized pricing,
precision medicine
and predictive equipment maintenance schedules.”

No matter the industry, big data has a key role to play in moving the needle for companies,mobile-app whether large or small. And that goes for companies currently unable to determine what their “big data” is. The unrecognizable could be customer sentiment in social media, server logs or clickstream data.

“Once you have identified untapped sources of data,” Kahn said, “you can use tools like Hadoop and NoSQL to analyze it.”

Matz broke down, by industry, what that ability to analyze could mean.

In the Commercial Sphere

In the commercial sphere, if a company knows 10 or 100 things about you and your situational context, then that company can do a far better job offering you something relevant to exactly where you are and what you might be interested in, increasing their opportunity to capture your respect, attention and dollars.

In the Industrial World

In the industrial world, if a manufacturing company knows where equipment is operated (hot and harsh climates versus moderate climates), as well as how that equipment is being used (lots of hard-braking) and collects data across a large fleet, then it can predict maintenance before costly breakdowns, saving millions of dollars — and it can price warranties more accurately, as well as improve designs and manufacturing processes.

In Pharma and Healthcare

In pharma and healthcare, evidence-based outcome studies that integrate genomic data, phenotypic data, clinical data, behavioral data, daily sensor data, et al., can lead to more targeted and effective treatment and outcomes for both wellness and illness.

Attivio has been using big data in one of the most vital ways by focusing on detecting military personnel who are at risk for suicide.

But, of course, big data still comes with challenges. Riaz acknowledged the reality, which is that every large organization is comprised of disconnected silos of information that come in all different formats; let alone the various business units, applications, protocols, information repositories, terminologies and schemas that doesn’t always mesh.

program-hero-strategic-analytics“Just dumping data into these unorganized but separate systems is anarchy and an egregious waste of time and money,” Riaz said. “Yet, this is how many technologies address the problem. It essentially just creates another big silo for the information to live in.”

Moving forward, additional ways to combine structured and unstructured data, as well as merge data from within an enterprise to data from outside of it, will need to emerge. And when it does, the impact will be glaringly obvious.

As Riaz posited:

The time to solve big problems with extreme information is upon us. Businesses, organizations and governments are putting a lot of faith – and money – into technology solutions to help them make sense of it all. As a technology industry, we owe it to these companies to deliver real products that deliver real results to real problems, not just create more work.

So, let’s start by making that first big decision: Understanding big data’s importance, no matter how big of a buzzword it’s become.

Click here to subscribe to our blog!

Footerindesign

Protected by Akismet
Blog with WordPress

Welcome Guest | Login (Brandeis Members Only)