What is Happening?
ISVs can, should, and do profit from the use of advanced data analytics – not only by integrating them within software and services offerings, but more importantly, by integrating an increasing range and scope of data (including Big Data) and analytics into their own business operations and decision making. Data regarding user behavior, operational efficiencies, and relationship management can and should be analyzed to help determine and take advantage of customer / buyer desires and needs, as well as competitive abilities, solution improvements, development strategy, upsell / cross-sell opportunities, pricing, business models, and hiring / retaining the most useful employees.
These were among the lessons reported by Saugatuck Research Fellow Bruce Guptill, who had the pleasure of attending and participating in this week’s “Deciphering the Data Storm” event, presented in Boston by the Software & Services division of the Software and Information Industry Association (SIIA).
Key lessons learned and reported by ISVs regarding the analysis and application of a wide range of business data (including Big Data) include the following:
- Data needs “gravity” in order to be useful; i.e., data needs varying combinations of human business context, situational relevance, and environmental semantics (i.e., “the voice of the author”) in order to be qualified, let alone be useful in analysis.
- Don’t always focus on reducing / limiting the “bigness” of data. Adding to / augmenting data with similar, complementary, and relevant data can provide and improve the “gravity” of that data. The key information sought may not be found completely in your own data. That being said, don’t be afraid to apply a variety of filters to screen Big Data; just be willing to accept failure and move on quickly when the filtering doesn’t work as expected.
- Share data in common to improve collaboration. “Success” is defined differently everywhere, even within small ISVs. Utilizing common sets of data has more beneficial impact, and enables more and better business collaboration, than trying to develop and focus on a “single version of the truth.” Different groups will always have different perspectives, and use data in different ways; ensuring that the data used is common rather than simply absolute will enable better understanding, and foster more (and more useful) interaction.
- Know what the next step is. In other words, set realistic business goals beyond simply analyzing data. Once deeply into the analysis, it’s easy to lose sight of business reasons behind the analysis. And as more data becomes more readily available from more sources, it becomes more and more easy to become overwhelmed.
Within just a few years, Big Data has become a driving force in enterprise IT, with projects springing up in every imaginable area of endeavor. It will drive processes as well as aiding in innumerable areas of information processing and discovery. But integrating Big Data with current infrastructure is problematic. To date, projects remain relatively discrete and can be based upon limited integration with data warehouses or separate operational data stores. But a more centralized and better-integrated solution is required as a basis for capitalizing on wide-ranging new opportunities. An important concept which is currently being developed is the “Data Lake,” which provides a repository for gigantic volumes of unstructured data in native format and may also include structured data to feed data warehouses. Continue reading
Strap yourself into your seat for the big data security analytics show, for it’s coming to a town near you. Carnival barkers from every walk of life will want you to come into their tents to see the latest and greatest show on earth: the big data security analytics show.
You will want to understand why using evolution charts, Venn diagrams, Pareto charts, and Pivot tables can or will help. You’ll want to see what association rules, clustering, decision trees, and forecasting can do for you. And you will want to understand the difference between analysis and knowledge, as it’s applied to security.
You will also want to make the distinction between whether you have to hire a data scientist or not and whether this will solve your immediate problems. You will also want to consider which approaches you could take that will produce the most value in the short, medium, and long term for your company and career.
To be useful, security analytics must take the large volume of data that can be collected and take three actions with the data, as follows:
- Reduce voluminous data and identify the pattern that matters,
- Use the information to enable a timely and appropriate in-situ response, and,
- Use the data to make adjustments – after the fact.
Perhaps geographic information systems (GIS), usually a specialized backroom capability, are emerging from the dark shadows of enterprise basements. The past year, saw notable changes and advancements in geospatial data and services relevant to Digital Business. These changes included integration of GIS with enterprise financial, sales, marketing, and collaboration systems and integrating enterprise development environments with location intelligence solutions to support Cloud location services.
Large-scale emergencies or disasters require sudden and dynamic resource allocation to meet the demands of geospatial professionals, related domain sciences, and the large amount of compute-capacity necessary to perform analytics on what can be terabytes of spatial data. Server-based solutions cannot typically fulfill the new access requirements. Continue reading
1. How would you define a Digital Business?
- A Digital Business or Enterprise is built upon digital technologies to create value for customers via innovative business strategies and interactive experiences that leverage an easy-to-use-and-access platform on demand.
- Internally, Digital Business empowers knowledge workers through data and collaboration, 1) enabling analytics-based insights and behaviors and 2) the ongoing enhancement of digital offerings.
- The foundation of Digital Business is the Boundary-free Enterprise, which is made possible by an array of time- and location-independent computing capabilities – Cloud, Mobile, Social and Data Analytics plus Sensors and APIs — with Integration as the glue to enable synergy and leverage business value.
- Digital Business should not be thought of in isolation, but rather as an ecosystem of the enterprise from 1) suppliers to buyers, embracing 2) business partners and technology partners and empowering 3) employees to serve their 4) customers and address their markets more effectively.
2. Why does having a digital business strategy matter for staying competitive?
- There is always a faster gun, a sweeter smile, a more convenient offer. Continuous enhancement of digital offerings is essential.
3. What are the main drivers requiring businesses to adapt by developing digital strategies?
- Better, faster, cheaper is just table stakes. We are talking about more innovative, more effective solutions that engage and retain customers. For two disruptive examples from the travel industry, consider Uber and airbnb. Uber, for example is a location-aware and pre-paid. The nearest car finds you, and the fare and tip are already paid automatically. An airport trip I took in Tampa was cheaper than the bus. airbnb is personal and intimate, but discreet and a bit of an adventure. Not too much, of course, because there are reviews, but it’s definitely not a manufactured hotel/motel experience.
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
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” 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
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
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 Report – Cornerstones 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