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Big Data & Business Intelligence Blog Posts - By Digital Management, Inc.(DMI)

Managing Merchant Attrition through Advanced Analytics - DMI. Data Rich Does Not Equal Profit: How to Do Data Monetization - DMI. Supply Chain Analytics in the Supply Chain Sector. MicroStrategy Symposium Series 2016 - Washington DC: Recap - DMI. Big Data Revolution and Data Monetization | DMI. Are You Using Your Data to its Fullest Potential? - DMI. Big Data Analytics: 5 Tips to Implement Analytics into your Business - DMI. Becoming a Big Data Storyteller. SAP Predictive Analytics. How Big Data is helping students graduate on time.

UC graduation rates are high, and growing Almost 85 percent of students who enter the university as freshmen complete a UC degree within six years. Graduation rates approach 90 percent including students who finish at a non-UC institution. The number who finish in four years has risen significantly, from 46 percent of students who enrolled in 1997 to 62 percent of those who started in 2010. As UC campuses look to better serve a growing number of California undergraduates, they are turning to a resource they have in abundance: data. New tools make it increasingly possible to capture, store and analyze data, supplying universities with minute details about their students, from what they missed on the midterm to how well they did in high school math. The trick is finding the connections amid this mind-boggling array of information, and using it to draw conclusions that can advance student success.

The campus has recently developed a Time-to-Degree Early Warning System. Data Rich Does Not Equal Profit: How to Do Data Monetization - DMI. MBAs Are Harnessing Big Data With The Internet Of Things — And B-Schools Showed Them How. The world’s elite business schools are hyped about harnessing the latest whizzy technological innovations. The internet of things (IoT) — the idea that every object, from selfie-taking fridges to toasters, can be connected to the net — is next on their bucket list. Gartner, the tech research firm, puts the number of objects that will be connected at 25 billion by 2020. Cisco says the figure is more likely to be 50 billion. Theos Evgeniou, professor of decision sciences and technology management at INSEAD, puts these bullish projections down to the advent of big data. He points to healthcare — a sector in which the IoT market is poised to reach $117 billion by 2020, according to “The digital revolution is having a monumental impact,” says Blake Long, chief clinical officer at Mosaic Health Solutions, who studied at Duke’s Fuqua School of Business.

Schools are taking stock from the swelling number of tech companies trying to come up with uses for their IoT technologies. Data Rich, Decision Poor: Monetizing Your IoT Investments - DMI. Big Data Analysis Is Changing the Nature of Sports Science. The best-selling book Moneyball by Michael Lewis changed the way people thought about sport, particularly for those owners, managers, and players with the biggest vested interests.

Lewis’s book helped bring about a revolution in which player performance was measured and assessed using an evidence-based approach rather than a tradition dominated by anecdote and intuition. Since then, sports scientists have attempted to replicate the success of this approach in sports such as basketball, soccer, American football, and so on. This science is driven by the relatively new ability to gather vast amounts of data about the players and the play while the game is in progress. However, in many of these sports, the capacity to gather data has not been matched by an ability to process it in meaningful ways. So an interesting question is what challenges sports sciences face in crunching this data effectively.

The sports these guys consider are together known as invasion games. Hospitality Industry Pushing the Envelope with Big Data - DMI. Managing Merchant Attrition through Advanced Analytics - DMI. DMI Big Data Insights. Big Data Platform Insights. Big Data Analytics: 5 Tips to Implement Analytics into your Business. Big Data Predictions for 2016. At the end of each year, PR folks from different companies in the analytics industry send me predictions from their executives on what the next year holds. This year, I received a total of 60 predictions from a record 17 companies. I can't laundry-list them all, but I can and did put them in a spreadsheet (irony acknowledged) to determine the broad categories many of them fall in. And the bigger of those categories provide a nice structure to discuss many of the predictions in the batch. Predictions streaming inMapR CEO John Shroeder, whose company just added its own MapR Streams component to its Hadoop distribution, says "Converged Approaches [will] Become Mainstream" in 2016.

The so-called "Lambda Architecture" focuses on this same combination of transactional and analytical processing, though MapR would likely point out that a "converged" architecture co-locates the technologies and avoids Lambda's approach of tying the separate technologies together. It’s About Real-Time! 5 Metaphors for Big Data and Why They Matter. Bernard Marr From the advent of written language, we have proof that we humans love to tell stories. Ancient myths were humans’ ways of explaining the world around them in terms they could understand. And while we may have moved past explaining natural phenomena like rainbows and earthquakes with stories, we have taken this method of understanding and explaining the world and applied it to difficult concepts like quantum mechanics, economics, and big data.

As a field, big data is rife with metaphors that help the initiated explain it to the layperson. But just as ancient myths got some things wrong when it came to explaining the world, we have to be careful with the sorts of metaphors we use to explain big data, and what the terms actually mean. As you can see from the following examples, some big data metaphors hit the mark, and some don’t. Machine Learning and Artificial Intelligence Data Tsunami, Flood, or Deluge Data as Oil, Gold, or Other Valuable Resources Data as Food ‘Big’ Data. Big Data: Payment Processors Hold the Key. How the U.S. Government Plans to Lift the Economy With Big Data. © Time Inc. All rights reserved. is a part of the network of sites. Powered by VIP Email address or Password is incorrect Forgot Password? Want the Full Story? Privacy Policy Thank you for your interest in licensing Fortune content. 1.

Mobile Business Intelligence: Look Before You Leap. Leveraging Big Data Big Time. Are You Using Your Data to its Fullest Potential? Five Ways to Invest in Privacy. Public perception of privacy and security in the post-Snowden era has changed, leading to end users caring vastly more about the topic. Last year, there were more breaches than ever before; ad-tracking technology has grown and will keep growing, collecting more and more data; and awareness of government access to personal data has increased.

Although it is still difficult to fully understand the long-term consequences of data collection at this level, the concerns are rising both from a user and a collector point of view. End users, whether they are employees or customers, are requesting a higher level of respect towards their privacy and putting forward more questions as to how and why their personal data is handled. Data collectors, whether they be application or website developers, must be aware of these growing concerns and take appropriate steps to address them from the ground up; building best practices in privacy into the products and services they provide. 1. 2. 3. 4. 5.

Big Data Revolution and Data Monetization | DMI. Big Data and HR: Why HR Needs to Enter the Game. 1 week agoBig Data and HR: Why HR Needs to Enter the Game By: Cathy Missildine, Co-Founder of Intellectual Capital Consulting, Inc. & President SHRM-Atlanta Originally published at Use Code PATIMES15 for 15% off a two day pass or combo pass. (Excludes workshops & All Access) Big data is everywhere. For years, big data seemed to be for the data geeks and the super quant jocks, but today it’s used in marketing, customer service, operations and even human resources. If you haven’t explored the benefits of big data it’s definitely time. “Big data” describes the sheer volume, variety, and velocity of data that resides in most companies. In this two-part series we’ll discuss WHY HR needs to enter the big data game and HOW HR can begin playing the big data game. Why does HR need to leverage big data? According to Harvard Business review, 71% of CEOs surveyed believe that human capital is the TOP contributing factor to sustainable economic value.

It’s all about the talent. Big data’s $1.6B role in DOD’s IT strategy. Special to FedScoop: A look at the Defense Department's big data plans as outlined at immixGroup's recent FY 16 Big Data Sales Opportunities at Federal Agencies. It's become undeniable that big data technology is an essential part of an organization's overall IT strategy. The Defense Department is expected to spend nearly $1.6 billion on big data in fiscal year 2016 to cover areas such as cyber defense analytics and situational awareness. Civilian agencies are spending even more, with an estimated $2 billion going to big data solutions and services. In the wake of a number of highly publicized cyber attacks, federal agencies are opting for more robust security approaches. Security is evolving from solely network-centric systems into more comprehensive systems integrating data analytics that go beyond traditional data sources.

The benefits go beyond security as disparate data sources are compiled and explored, revealing new areas for research and ways to optimize device performance. Mobile Apps: The Miniaturization of Big Data. What is Big Data? Big Data is a phrase used by many large corporations today to describe extremely large datasets, sometimes on the order of petabytes (1,024 terabytes) or exabytes (1,024 petabytes), that are so large they are difficult or impossible to process using traditional tools and databases.

In some cases, it is not the size of the dataset that causes it to be referred to as "big data"; it is the speed at which the data is captured or made available that is too large to process or filter using conventional means. And sometimes, organizations use "big data" to mean not the data itself, but the technology or resources used to store it or process it. As such, it is an amorphous term that at this point in time has no fixed meaning, but generally refers to previously incomprehensibly large data and the technology used to manage it.

What is Hadoop? What is Business Intelligence? Mobile Apps for Big Data Some companies using mobile apps for Big Data include: Guess? Is It Safe? Integrating SAP BusinessObjects Reports into a PHP Portal. Turning Data Into Actionable Insights. Taking Advantage of Your Data in the Connected Marketplace. DMI Collaborates with Google Cloud Platform on Mobile App Development and Big Data.

BETHESDA, Md., April 22, 2015 /PRNewswire/ -- With the explosive growth of mobile applications and services in the enterprise, CIOs and IT directors are faced with a myriad of different environments that need to be managed, monitored and maintained throughout the lifecycle of their corporate apps. After the successful launch of over 50 global customer implementations that leverage Google Cloud Platform and three years of joint insight and training workshops in Europe, DMI announced today it is expanding its Google Cloud Platform collaboration to North America.

Accelerating the transition to the cloud: Because Google Cloud Platform provides one of the most powerful and scalable cloud solutions available today, DMI is able to deliver mobile services that include native apps, responsive web, back-end and back office, as well as big data analytics. PR Contacts:Kim Dearborn Nadel Phelan, Inc. 831-440-2407 Alika Nagpaul DMI 240-200-5852 Big Data Insights. Welcome to Forbes. Reimagine the Future of Business with the Internet of Things and Big Data | SAPPHIRE NOW ONLINE. Google Cloud Dataflow Makes Big Data Offerings Even Bigger. In the latest of a string of cloud upgrades, Google on Thursday revealed automated data-processing features that the company hopes will encourage users to adopt its cloud for their big data and analytics needs. From the Hadoop Summit in Brussels, Google launched a beta version of Google Cloud Dataflow, a managed logic-processing service.

The Internet giant also unveiled upgrades to its popular BigQuery analytic platform, including new European zones. The big data capabilities allow users to gain insights from their data without having to worry about managing hardware infrastructure and system administration, wrote William Vambenepe, a product manager at Google, in a blog post. [Related: Google Bulks Up Cloud Networking Capabilities] "The promise of big data is faster and better insight into your business. The big data functionality comes to Google's cloud just days after the release of several new networking features. Big Data Analytics A Practical Guide: Step 3 – Following Your Plan To New Insights.

Data Dating: Finding the Right Partner to Take Your Data to Market. DMI in another Forrester Report! What are this year’s top retailers doing that you may not be doing? The days are shorter, the weather is colder but the shopping… well that’s just starting to heat up. As retailers hit us with their best Black Friday campaigns and in-store promotions, who were the ones that stood out? More and more the retailers with the competitive edge during this festive season are those that are using big data analytics to help them refine and sharpen their strategies. Here are the top ways that retailers today are using Big Data to help them this holiday. 1. 2. 3. 4.

Additionally, while today’s holiday shoppers are ready to spend, retailers must remember that it is personalized messaging that cuts through the snowstorm of promotional clutter. If you are interested, please see our white paper “Beating Amazon – Traditional retailers are well positioned to win against online-only retailers. . - Thiag Loganathan, President, Big Data Insights Division Back to Blog.

Big Data Revolution and Data Monetization. What once was a hyped term and a far out concept has now become a widely adopted practice in organizations big and small. The Big Data revolution began as companies started making investments towards adoption of data management and analytics. However, with new terrain come new challenges and companies are still struggling with how best to create a big data strategy and extract meaningful insights and value from the data. As we approach the second wave in the age of Big Data, companies are now scrambling to identify just how to measure the ROI of their investments and over what period of time.

The new question to ask now is “How fast can we generate returns from our big data?” It’s no surprise that companies who have already adopted a big data strategy are now looking to data monetization to answer a piece of this question. A great example of what I mean is found in the relationship between retailers and suppliers. To read more on Data Monetization Back to Blog. Big Data: Payment Processors Hold the Key. The payment processing landscape has changed and the old ways of doing business are rapidly becoming obsolete. For merchants accepting most forms of payment is a necessity, but card processing carries a cost. In today’s competitive economy, even small costs loom large for merchants – so there is constant pressure to reduce the cost. Every time a contract renewal comes up, merchants are constantly looking at ways to reduce their price.

The continued commodization of payments coupled with disruptive new entrants like Square, are forcing companies to rethink their business models. Merchant attrition has become one of the biggest concerns for merchant acquirers and independent sales organizations (ISOs) because it can take as many as three new accounts to overcome the diminished value of a single, lost merchant account. The good news is that payment processors have an untapped gold mine with the loads of data that they continuously collect, which can provide a unique advantage. Back to Blog. Upgrade to SAP BO BI 4.0 or not? Supply Chain Analytics in the Supply Chain Sector.

The Importance of Big Data Storytelling. The Difference Between Analytical BI Strategy and Operational BI Strategy. Integrating SAP BusinessObjects Reports into a PHP Portal. Pin by Digital Management, Inc. (DMI) on Big Data & Business Intellig… Business Objects SP5 BI Mobile Dashboard Support for iPad. Thoughts on BusinessObjects Edge BI 3.1.

Thoughts on Mobile BI. SAP BusinessObjects Mobile for iPad 4.0.3. Upgrade to SAP BO BI 4.0 necessary? Going Mobile: SAP BusinessObjects Explorer for the iPad.