Tag Archives: big data

How Mobility and Big Data Empower the Boundary-free Enterprise™

Traditionally, mobility was a means of personal interaction and accessing business systems, data, and operations. Mobile technology means more than just personal enablement. Now, mobility is also a means of gathering/producing business, which in turn generates and requires an increasingly wide and deep volume and variety of data. For example, businesses can improve their customer engagement by using mobile devices to collect more feedback around the customer experience. Some mobile applications use location to expand and improve marketing efforts to customers. There is a global surge in mobile payments both via card scanners and mobile money.

It’s not just mobile phones and tablets; wearables and sensors on movable items such as vehicles and retail goods contribute to the mix of devices generating and consuming data and bandwidth. Accompanying the resulting deluge of data is uncertainty. Uncertainty abounds concerning data volumes, network capacity, security, privacy, and other processing requirements. Cloud implementations can help address this uncertainty by handling the fluctuating data and communications demands while ensuring availability and reliability. Continue reading

The Business Problem with Big Data Analytics

What is Happening?          

Recent software analyst and IT media reports, including insights from a recent SAP Americas User Group (ASUG) survey, suggest that SAP’s HANA Big Data service / platform is not yet seen by a majority of ASUG members as benefiting their business (relative to the implementation cost of implementing), or driving enough revenue growth for SAP. SAP has, very smartly, issued a careful rebuttal explaining how, where, and why customers see value in HANA – and more importantly, offering to work with any customer to help them understand and realize business benefits from the offering and its associated apps.

We believe that, through at least 2016, this type of approach is the most effective way of getting user enterprises to understand the value of any Big Data analytics capability; i.e., develop company-specific and operationally-specific business cases in order to enable and develop business value. This is because, in most companies, Big Data analytics just can’t be widely used to deliver broad-based business benefits across the full portfolio – because user enterprises have huge challenges finding and managing their own data, let alone analyzing it. Continue reading

Cloud Robotics: Robots of the World Unite

“Cloud Robotics” as a term is only a few years old, but the idea has been around for some time. If complex sensory tasks can be performed at a distance, then robots will need to have less bulky processing units on board. With expanding connectivity and higher bandwidths, some of the latency issues in this type of arrangement are being removed, and many vendors are looking at this area with renewed interest.

Robotics are essential to modern industry, and will play an ever-increasing role in daily life. Many, such as vehicles, will require some degree of autonomy. They will also require an ever increasing amount of processing and storage. The Cloud makes it possible to virtualize robot components and provide sensory and other solutions that can take advantage of the enormous facilities of Cloud IT. Robotic components can be virtualized and provided for interaction and download as a Robot-as-a-Service parts. Using the Cloud, moreover, provides access to all of the data and programming available on the Internet, and the ability to directly share learning between robots. It also makes it possible to coordinate robot teams for work on complex processes. Continue reading

Alteryx Inspire – The Importance of Analytic Context

Recently, Saugatuck attended the 2014 Alteryx Inspire event in San Diego as part of our ongoing Analytics, BI, and Big Data research. The event showcased not just Alteryx offerings and customers, but also did a good job of presenting and encouraging discussion around Analytics trends, partner relationships, and challenges for users of analytics – including Big Data. We came away from the event with three key insights, as follows:

1) ETL & Access to the Data. One of the primary differentiators of Alteryx is built-in ETL. Even though the application features significant Advanced Analytics capabilities (built around the R language), the Alteryx Designer focuses around an ETL-centric workflow. These capabilities make Alteryx adept at combining multiple data sources, and performing complex Joins and Transformations that would normally be prohibitively difficult for end-user business analysts. These capabilities feature centrally for the customers that we talked to as well, as most Continue reading

Keys to Digital Transformation, Cornerstones for Digital Business

What is Happening?          

Digital delivery models are impacting traditional businesses. Driven by consumer demand for convenience and new consumption models, including subscriptions and usage-based consumption, enterprises are moving to Digital Business models and offerings, and finding huge upside from predictable revenue streams and long-term, recurring-revenue customer relationships.

There’s no simple means of accomplishing this, however – there’s no “silver bullet.” Saugatuck’s research in the constantly-changing, constantly-innovating world of Digital Business continues to indicate that success requires not only significant investment in business strategy, modeling, and organization, but also a flexible, platform-based approach built on three cornerstones: data analytics, dPaaS and other Cloud development platforms, and DevOps.

A 36-page new Saugatuck Strategic Research ReportCornerstones for Digital Business: Big Data, dPaaS, and DevOps – summarizes and explains this platform-based approach, using key concepts of Digital Business, in-depth explanation of the required platform architecture, and re-examinations of foundational Saugatuck research to illustrate and guide readers through Digital Business transitions. Continue reading

Zebra, Motorola, and the Internet-of-Things Reality

What is Happening?

This week Zebra Technologies, a $1B maker of RFID devices, sensors, barcode scanners, and other asset identification and protection devices and systems, announced plans to acquire the Enterprise business (including the Symbol business unit) of Motorola Solutions to, as stated on the Zebra website:

“…combine the complementary offerings of two industry leaders in asset tracking solutions to create a market leader in enterprise asset intelligence for the Connected Age. Motorola Solutions’ mobile platform captures real-time data about physical assets, people, and transactions across the enterprise. Zebra’s enabling technologies provide visibility into business operations for deeper insights and smarter decision-making. The companies’ shared commitment to innovation will help customers harness powerful technology trends like the Internet of Things (IoT), location and motion sensing and mobile enterprise cloud computing.”

On the surface, this appears to be yet another conceptual IoT play, helping to illustrate the scope of “things” that can be, will be, and are being interconnected to enable more business data, insight, and improvement. The total acquisition price is put at $3.5B – to date, one of the larger investments or acquisitions in the name of the “internet of things.” Zebra is borrowing more than $3B to make it happen, and only putting up about $200M on its own – expecting significantly increased revenue to pay off the deal in as little as three years. Continue reading

Big Data and Advanced Analytics Panel (CBS2013)

On September 25, 2013, Saugatuck held its 3rd annual Cloud Business Summit at the Westin Times Square in New York City.  As with prior Summits, our event brought together more than 100 large-enterprise CIOs, CTOs and senior business and finance leaders – to explore how they can and are realizing value from the Cloud. This year’s conference theme was “Rethinking Business Innovation.

One of the hottest topics in Cloud business today is Big Data and advanced analytics. While many current attempts and instances are still trials and PoCs, as enterprises work to figure out what these “power tools” can really do – significant progress and payback is being demonstrated in analyzing purchase decisions and in the targeting of customers, and in leveraging sensor data to help drive operating efficiencies throughout industry and the supply chain.

In this featured panel, Saugatuck Technology SVP and Head of Research Bruce Guptill is joined by Will Klancko, Sr. Risk Program Manager at GE Capital, Hodan Hassan, Managing Director at Unicef Continue reading

The Coming Big Data Tsunami in Finance

Industry research, including work done for clients by Saugatuck Technology, has consistently indicated a lag in adoption of Big Data and Advanced Analytics within the financial area – including Finance processes in business, and in the Financial Services industry itself. This has been attributed to natural caution regarding this data and these activities, so central to business. But the reasons for this lag go deeper, and are more complex than might be supposed. In consequence, as the Big Data revolution begins to fully engage finance, there are likely to be significant repercussions, and great opportunities for vendors.

The Financial Services industry and the enterprise Finance function are inherently linked. In some large companies, there is little difference between department operations and those of an investment firm or a small bank. New technologies and concepts are tested in both environments, creating a healthy cross-pollination of innovation. Shared issues include the need to optimize investments, special regulatory concerns, special security concerns; and a host of measures for understanding, measuring, and predicting financial results. Continue reading

Managing Risk, Big Data Style

Although Big Data and Risk Management would seem to be a marriage made in heaven, risk management generally tends to lag in advanced analytics adoption. There are numerous reasons for this, starting with a reluctance to tamper with financial processes, and going on to the central risk management difficulty of predicting uncertain events. Big Data reluctance is seen most easily in the Insurance sector, where businesses are built upon risk management—yet practitioners are averse to using analytics tools which do not readily yield a predictive result. In fact, the debate rages on as to whether calculating risk is an art or a science, and recent advances in Big Data are only just beginning to move the needle more toward science.

The base problem is that data of a single type alone, no matter how significant the amount, cannot help much in the prediction of events outside of the data perimeter. Risk management is about estimating possible unfortunate effects and considering their possibilities and mitigation. In a limited space, such as IT alone, this is a highly simplified exercise. But, looking at the possible factors that might impact a business, the range is simply too wide, and it is difficult to even locate significant events within the data. Continue reading

Predictive Analytics: Knowing What Already Happened Isn’t Good Enough Anymore

A new Strategic Perspective published for Saugatuck Technology clients looks at how and why simply reporting on what has already happened, or monitoring various aspects of a business, is unlikely to provide adequate insights needed to make high-impact decisions and to better the competition. Enterprises are therefore combining internal operations and external data streams in new ways, which is blurring the traditional lines between these two entities, while providing new actionable information. The result: Fast-growing interest in Predictive Analytics, especially as regards using Big Data. Many businesses have and are moving to predictive and prescriptive analytics as a way to get better returns on their Big Data investments by determining causation from predictive analytics. Continue reading