Digital Empowerment and Transformation

Organizations must adapt faster than ever to remain competitive. Enterprise leaders, including CIOs and other IT leaders, must transform their organizations with nimble digital solutions and processes to thrive.

Key drivers of digital transformation include:

  • Better-informed, increasingly demanding customers.
  • A mobile workforce requiring new types of connectivity.
  • Massive new data streams and increasing storage needs.
  • Rising cybersecurity threats and strict compliance regulations.
  • Opportunities for increased workload efficiency.
  • Flexible IT consumption models.

    To meet these challenges, organizations are recognizing the need to
    adopt an enterprise cloud strategy. By enabling increased flexibility
    and mobility in the business model, a cloud investment can serve as
    a foundational component of digital transformation.

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    It is no secret that cloud adoption is steadily increasing. The factors driving
    investments in enterprise cloud are numerous, diverse and unique to each
    organization. The pressure to adapt can lead enterprises to attempt ad hoc cloud
    deployments, expecting a broad implementation to serve as a panacea.
    Instead, unfocused deployments often result in excessively complex IT
    environments that fail to achieve the desired business outcomes.
    In many cases, IT departments that funnel capital into a private cloud end
    up spending more time building and maintaining their cloud solution than
    leveraging it for cost savings and data-driven decision-making. To improve
    investment quality, the question then becomes: How do organizations ensure
    that their approach to enterprise cloud has the right balance of upfront
    investment, immediate utilization and ongoing value?

Why do I need to go mobile?

Is delivering mobile applications really worth the eort? Will mobile applications really add value to the business? It is clear that mobility brings improvements to the enterprise in terms of efficiency and lower operational costs. This means that by investing in a mobile strategy, employees are given the tools needed to make better and faster decisions.

Better yet, there’s evidence that investing in mobile pays. In a recent Forrester survey. 75% of decision makers indicated that deploying mobile apps had increased worker productivity, while only 65% acknowledged that mobile apps increased responsiveness and decision making speed. Mobile is not a shot in the dark; it’s something that has already proven its benefits.

The way mobile apps achieve these bene-ts is by providing access to relevant information at the right time and place, in an easy-to-use, consumable and actionable form. This gives workers the insight and tools needed to accomplish more.

Employees are aware of this productivity increase and they’re the ones driving the mobility trend. They bring their own mobile devices to the workplace and expect to be able to access applications from their devices.

 The challenge is building and maintaining these applications in light of the evolving technology and device options.

There are a lot of technologies out there to help enable mobile strategies.

There are frameworks, IDEs, debuggers, emulators – the works! But before deciding on a mobile approach, a decision should be made on the type of mobile application to build.


Multi-Path Networking Is a Key to Maximizing Cloud Value

Computing has gone through several major evolutionary steps since its introduction as a mainstream corporate resource. In the 1960s, businesses oriented their compute strategies around the mainframe. This gave way to minicomputing, which eventually ceded its role to client/server computing. Today, the industry is in the midst of another major revolution—the shift to cloud computing. The cloud is the fastest-growing part of IT today. In fact, the ZK Research 2015 Global Cloud Forecast predicts the cloud to grow at an 18% compound annual growth rate from 2014 to 2019—that’s more than six times the 3% rate of growth for the rest of IT during the same period. Each computing transition has had a profound impact on IT in multiple ways. First, the cost of processing power and storage has continued to drop by orders of magnitude. Also, the network’s role has escalated in importance with each shift. In the client/server computing era, the network was a tactical resource that connected PCs to servers and offered no real competitive advantage. In the cloud era, the network becomes a strategic asset and the basis of competitive advantage. The shift to the cloud enables organizations to become more flexible and adaptable and to take advantage of changes in the business environment. However, organizations can only be as agile as their least agile IT component— and, in most cases, that’s the network. If businesses are to truly harness the power of the cloud, it’s time for the network to evolve.

The architecture used to build most networks today has been in place for well over three decades. The traditional “hub and spoke” model was designed for client/server environments where almost all of an organization’s data and applications resided in the data center (i.e., the hub location) and were accessed by workers in branch locations (i.e., the spokes). Internet traffic would enter the enterprise through a single ingress/egress point, typically into the data center, where it would then pass through the hub and then to the users in branch offices. This wasn’t ideal because any kind of information that had to be sent back to the Internet would need to traverse that same spoke and then pass through the data center and back out the Internet connection.

The Disruptive Data Warehouse

The data warehouse has been undergoing a continuous evolution. It integrates the best existing technologies and makes them easy to use, while embracing new technologies in an intelligent, cost-effective manner. It gives more business users access to your data. And it lowers the barrier to entry, putting innovation within any organization’s reach. It is a disruptive data warehouse.



Today, organizations have different types of data sitting in various repositories and databases. The disruptive data warehouse has evolved to query these different repositories and perform various types of analytics. But it isn’t just querying multiple systems and aggregating the results. The disruptive data warehouse automatically integrates processing across all the various engines. The processing is pushed down into the various repositories, and the results come back to one place where the processing is completed and the data is served to users at scale.


Today’s data warehouse is dynamic. It’s interactive. It’s for anyone who needs to analyze data—your BI team, data scientists, IT professionals, front-line workers, executives, business analysts, developers—everyone. The disruptive data warehouse is built on the premise that there are dozens of usage models, and they all require an operationally robust means of serving data. In addition to serving BI reports, the disruptive data warehouse serves as a forum for executing diverse analytic’s, including via scripting languages, to interact with the data and discover nuggets of information that can help the business.

New School: Yes—and JSON, XML, weblogs, and more

Today, in addition to structured data, organizations collect unstructured and semi-structured data. A disruptive data warehouse provides unprecedented flexibility, allowing you to store data as first class objects. You’re not limited to rows and columns of structured data. You can store semi-structured data, like XML, JSON, and weblogs, natively. Methods within the database can operate on all data types, delivering the value of integrated data. Given the variety of data, modeling every possible combination isn’t always feasible—or necessary. With a disruptive data warehouse, modeling can be performed when it is appropriate. Not sure what the business value will be of a voluminous big data flow and can’t justify the time to model it? No problem. Store it affordably in a data lake, such as Hadoop or a high storage density RDBMS that handles these data types, and create the schema at the time of access. Or move a portion of the data to the data warehouse to analyze it and determine its business value

Small Thinking About Big Data

It is time to end small thinking about big data. Instead of thinking about how to apply the insights of big data to business problems, we often hear more tactical questions, such as how to store large amounts of data or analyze it in new ways. This thinking is small because it focuses on technology and new forms of data in an isolated and abstract w


  • Big data is really just “data.” What’s the best way to handle all our data?
  • Big data is one piece of a larger puzzle. How can we effectively combine it with existing analytics to yield the greatest impact?
  • Big data needs to enhance business operations. How can we use big data to create better products and services?

Big data doesn’t mean that we must hit the reset button. We still need to harvest information from enterprise applications and construct a comprehensive structured model of our business. We need to securely manage information as an asset. We need to control access to data to protect privacy and comply with regulations. And we need to enable everyone to explore as much data as possible. Big data doesn’t mean we flip the off switch on all past business intelligence (BI) activities. It means that we understand how to

We must remember that big data isn’t about technology; it is a movement, a mind-set, that’s ingrained in an organization. How can we channel the energy that surrounds big data into a cultural transformation? Movements don’t succeed without a compelling vision of the future. The goal should be to create a data culture, to build on what we’ve done in the past, to get everyone involved with data, and to derive more value and analytics from all the data to make business decisions. This is the real victory to do a better job with everything we have by adding new capabilities

Starting a big data movement involves challenges:

  • Transforming company culture to be data-driven and compete on analytics
  • Discovering nuggets of information about customers, products, and performance across systems and data formats (ERP, legacy systems, web logs, email, voice, text, social media, and more)
  • Making data and analytics accessible to as many people as possible

The right vision for each company will differ, but for most companies a movement should be characterized by:

  • Using business questions, not technology capabilities, to drive the architecture
  • Increasing self-service access to data to encourage data-driven decisions
  • Enabling fast, iterative discovery that allows analytical teams to “swim” in the data and see what signals or trends emerge



A Guide to REST and API Design

In his 1966 book “The Psychology of Science,” American psychologist Abraham Maslow tackled the idea that those in the field of psychology needed to approach treatment from multiple perspectives, to take on new ideas, and not just continue using the same theories and techniques created by Freud and his followers so many years ago. Acknowledging that changing your point of view can be difficult, Maslow wrote It is tempting, if the only tool you have is a hammer, to treat everything like a nail.” We have all had this experience. We get so used to the way things have been done in the past, we sometimes don’t question the reasons for doing them.

It may seem curious to refer to psychology in a work on REST and API Design, but it works to illustrate two distinctive points:

(1) that all design decisions, regardless of whether they pertain to software or architecture, should be made within the context of functional, behavioral, and social requirements—not random trends; (2) when you only know how to do one thing well, everything tends to look identical.

“If all you have is a hammer, then everything looks like a nail.”

—Abraham Maslow, The Psychology of Science


Don’t Let the Cloud Obscure IT Transparency

Business leaders look to the CIO to be the broker of cloud and other IT service providers. But this presents new challenges to all IT leaders, even those who have already achieved IT transparency across their portfolio of products and services. Instead of taking a step in the wrong direction in this new cloud era, proven IT financial management strategies, if used correctly, will empower IT leaders to succeed amidst these new challenges. This technology dossier examines the challenges of cloud transparency and sets out a roadmap for bringing performance and financial manage-ment practices to shared services organizations.

The CIO role has changed. CIO’s “State of the CIO” survey found 72 percent expect that with-in the next three to five years they will become more focused on business strategy, compared to today, where 52 percent are focused on transfor-mation and 22 percent are focused on functional issues. Obviously, this new business strategy fo-cus will include cloud. CIOs must adopt method-ologies to provide transparency and in order to succeed in this new cloud era. But it will be diffi-cult to make that transition if IT is unable to prove that it is getting the best value for IT expendi-tures in a way that allows more resources to be spent to improve efficiency and drive innovation. The ability to efficiently manage and opti-mize cloud services is a critical aspect of man-aging IT like a business. ITFM transparency ini-tiatives can demonstrate how IT is improving its collaboration with financial management and business consumers.

Automating costing, budgeting and forecast-ing, consumption reporting and demand man-agement capabilities is essential to analyzing and managing IT costs and the value of services deliv-ered. But that may be even more difficult due to differences in the way providers account for their cloud services delivery.


“If a company is using Amazon Web Services, Microsoft Azure and IBM Cloud Services, each one provides billing data differently, so it’s difficult to get a holistic view across all vendors,” said Bob Svec, SVP of ComSci and PowerSteering product lines at Upland Software. “ComSci can normalize the data across all the cloud providers and deliver various views across all vendors and lines of busi-ness. This also enhances an enterprise’s contract negotiations as they can leverage information from all vendors.”





CIOs today have more responsibility than ever for fulfilling the business objectives of their organizations. Among the strongest shared business objectives for IT and business leaders:

  • Increasing revenue growth
  • Reducing operating costs
  • Driving Productivity improvements

1. Greater agility, standardization and modernization within IT are key facilitators to achieving these business goals. Key Technologies are being adopted to achieve these goals–not only in the cloud and big data sets but also the implementation of the next-generation data management platforms running on interoperable and reliable operating systems and hardware.

The combined solution of SAP HANA running on Red Hat® Enterprise Linux® for SAP HANA® on Dell platforms addresses these business and technology drivers in a highly integrated, tested and high-performing solution.

Key Enablers to Achieving Business Goals

New technologies in and of themselves are important only to the extent that they produce positive business outcomes. For example, showing how in-memory technology can speed up analysis of marketing campaign results to get better insights into how advertising budgets should be realigned and distributed is a relevant business outcome aided by technology. When contemplating new technologies—and their potential value to the enterprise—it’s important to map them to these common enterprise IT goals: agility, standardization and modernization



Cloud Migration

Moving to the cloud can be cost-effective. At the same time, the challenges and risks of doing so are significant and, in many cases, are preventing companies from being as agile as they would like in terms of moving to the cloud. Data migration is the top challenge (see Figure 1), with application migration not far behind.

It has always been the case that changes to production are risky, even with applications hosted on premise. On average, approximately 60% of production-related performance issues and outages are related to changes in either hardware or software. Cloud carries even higher risk, particularly when IT organizations lack the visibility into cloud systems necessary for pre-planning and decision making.

There are a host of decisions to be made in the migration process, some common to virtually all types of cloud services and others specific to hosting services such as IaaS. IaaS, software as a service (SaaS), and PaaS migrations, for example, all require planning in a variety of key areas, including the following:

  1. Vendor selection
  2. Migration planning (if moving from on-premise to off-premise hosting)
  3. Integrations
  4. Network sizing
  5. Service Level Agreements (SLA) and associated monitoring

IaaS and PaaS consumers have these additional considerations:

  1. Cross-provider service and cost comparisons
  2. Architecture considerations, such as code and data locations
  3. Data privacy
  4. Provisioning of hardware and software
  5. Skills development
  6. Performance/availability monitoring

Data privacy and migration support are the top factors IT professionals cite as important to making vendor selections (see Figure 2). The migration process is considered to be so risky, in fact, that some consumers have opted to go the pricier service provider route since expertise in supporting data and application migrations is a key value proposition of service providers.

However, achieving the cost savings of a true “cloud” IaaS, such as AWS or Azure, requires companies to develop the expertise necessary to take a hands-on approach, which requires clear visibility into both the existing systems and the new cloud service. Such visibility is delivered by “cloud-ready” enterprise management tools, such as New Relic.




FBI smashes bazaar Darkode

The FBI in concert with Interpol and other worldwide law enforcement teams say they have taken down the international cybercriminal site marketplace Darkode and arrested 70 people involved with the site. Darkode was an online, password-protected forum in which hackers and other cyber-criminals convened to buy, sell, trade and share malware, ransomware, information, ideas, and tools to facilitate unlawful intrusions on others’ computers and electronic devices, the FBI said.

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 Before becoming a member of Darkode, prospective members were allegedly vetted through a process in which an existing member invited a prospective member to the forum for the purpose of presenting the skills or products that he or she could bring to the group. Darkode members allegedly used each other’s skills and products to infect computers and electronic devices of victims around the world with malware and, thereby gain access to, and control over, those devices, the FBI said.

“Of the roughly 800 criminal internet forums worldwide, Darkode represented one of the gravest threats to the integrity of data on computers in the United States and around the world and was the most sophisticated English-speaking forum for criminal computer hackers in the world,” said U.S. Attorney David Hickton in a statement.   “Through this operation, we have dismantled a cyber hornets’ nest of criminal hackers which was believed by many, including the hackers themselves, to be impenetrable.”