Techaisle Blog

Dropbox, Carbonite and many others have accelerated the use of Cloud storage in the consumer market for backup of music, photo, file sharing and more recently with various social networking needs and media sites. Similarly, Box.net has established its strong presence within the business segment. Techaisle’s SMB and mid-market business MarketView forecast shows that cloud storage will be a US$1.1 Billion market by 2016 growing at a 37 percent CAGR.

It would not be out of place to say that businesses are always very concerned about regulations and business policies requiring them to retain data for longer periods. Add to this the intricacies involving data protection via backups and replication, data scalability requirements and data availability needs across multiple geographies - the complexities and cost with storing massive amounts of data that is generated across the enterprise becomes huge.

Though it has limitations, an object based Cloud storage solution addresses many of the business challenges above – a scalable, easily replicable, pay-as-you go solution that is geographically accessible through public internet solution, thereby meeting businesses’ most demanding requirements with respect to their data storage policies.

Given the cost competitiveness, scalability and security attributes, backed by enterprise grade SLAs, Object Storage in the Cloud is an extremely viable option for the small and medium businesses (SMBs) looking to migrate their datacenters into the Cloud. RAID arrays are mostly used by mid-sized businesses but that is no protection against a disaster or any malware attacks.

What is Object Storage and why it is significant for mid-market businesses?

An object Storage solution breaks storage data into distinct segments, or ‘Objects’, each containing a unique identifier (or metadata) that allows data retrieval.

Valet parking is often cited as an analogy for Object Storage. When parking at a garage, the attendant gives a claim ticket that identifies the car that allows the driver to pick up the car later. The driver is not concerned where the car is parked as long as it is identifiable when it is time for pick up. Object Storage, likewise, stores data (objects) and retrieves when required based on its unique identifier.

Object Storage differs from traditional Storage Area Network (SAN) or Network Attached Storage (NAS) in that the former is ‘Object Based’ and has the following characteristics:

• Each object has its own ID, metadata, data protection policy and is unlike any file system where files often inherit attributes from their parent containers/files/directories.

 

• There is no limit on volume restriction of size of file systems – unlimited scalability, not limited on infrastructure capacity maximums.

 

• Data is accessible anywhere over HTTPs - availability of the service can be anywhere on the internet. Hence this is latency sensitive.

 

• Data is typically retrieved via a RESTful or SOAP based API Web service. Storage vendors have their own proprietary API platforms – e.g. Amazon S3, Nirvanix APIs, OpenStack or EMC Atmos platforms. Any programming language that supports web service-based API calls to remote systems can be used to build applications around the storage solutions.

 

• Price, which is normally based on usage, is much lower than traditional Block and File storage solutions. Businesses typically pay a per-gigabyte rate for upload and download and a per-gigabyte fee for monthly storage. In addition, some providers charge for each data access request based on reads, writes, etc.

Use Cases

• Data Archiving and backup: Retain data that needs to be easily accessible and always available but is not constantly used in real-time.

 

• Data Compliance Requirements: Must keep data safely and reliably for audits, reporting, regulatory compliance, discovery, backup and restore, or disaster recovery.

 

• Data accessibility: Have a library of content and/or media files that employees in many locations must access to download items. Also need employees in many locations to be able to upload or download files.

 

• Web 2.0 and Social Media: Manage exploding data growth or have fluctuating data storage requirements - Object storage systems have massive scale and provide moderate performance at low cost.

Medical Imaging and medical records applications also have massive use for Object Storage due to sheer volume of data storage requirements. Healthcare Vertical, particularly, have shown high adoption rates for Object based storage.

Competitive Landscape

The market is yet very fragmented though Amazon AWS Simple Storage Service (S3) is considered the leader in this space. Though it has challenges, AWS is a highly innovative service and has created AWS Storage Gateway that enables hybrid storage architectures that span both on and off premise storage options.  Nirvanix, a pure play Cloud Storage provider that offers public, hybrid or on-premise Nirvanix-powered storage services which are priced for various support levels. There are other big names such as Google, Windows Azure Blob, Rackspace CloudFiles, AT&T’s Synaptic Cloud Storage and recently Savvis has also entered the Cloud Object Storage space.

Vendors seek to differentiate themselves on price, quality of services (QoS), SLAs and hybrid architectures. At the same time they tend to gravitate towards some established storage and compute platforms to enable standardization, achieve economies of scale and allow for ecosystem build-up. This allows their business customers to combine their storage solutions with any third party solution that uses a similar platform. For example, AT&T Synaptic and Savvis are aligned with EMC Atmos Storage Platform, whereas providers like HP, Rackspace CloudFiles and SoftLayer are aligned wtih OpenStack platform. This enables any third party solution that is based on the above platforms to be combined with storage solutions offering any custom configurations. AmazonS3 is an exception that is based on its own AWS Storage Gateway.

Techaisle Take

Justifiably, there is a great deal of hype today around Object Storage, especially relating to its Cloud, Social Media and Big Data applications. However, it is important to understand the specific use cases and workloads Object Storage can be useful for, given its limitations such as Latency sensitivity, lack of standardization among object storage interfaces and in some specific uses where the stored data is modified frequently and hence not suitable for an Object Storage solution.

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We have covered Marketing Automation as a major topic, especially through the Techaisle SMB Marketing Automation Study conducted in US, UK, Germany and several blog posts, commenting on the rapid growth and consolidation in the market. In one fell swoop Oracle is now addressing a US$3.5 billion opportunity in the US by 2015 and US$6.0 billion opportunity globally.

Oracle’s announcement that it would acquire Eloqua for $871M, a leading Marketing Automation vendor, seems a little odd at first, mainly because majority of Eloqua’s customers are said to be using Salesforce.com as their CRM platform, and because Oracle competes with Siebel-on-Demand and recently released its’ own Fusion CRM product.

In the typical Oracle fashion of acquiring existing market leaders, i.e. Siebel Systems, PeopleSoft and JDE, Oracle snatched up another jewel for the Ellison crown, apparently valuing B2B and Enterprise-level functionality over SMB and Social Media Marketing automation that have been the focus of arch-rival Salesforce.com. It also sends a message to Redmond, whose recent acquisition of MarketingPilot seems to offer a substantial list of features and functions, but does not carry the weight of Eloqua’s brand. In the short term, it kind of looks like a mixed bag; the repercussions of the purchase seem to revolve along these areas:

SMB Customers:

1)     Oracle says they will continue to support third party applications, but they have a huge vested interest in on-premise CRM in Siebel and other solutions that will compete for resources,

2)     Enterprise customers who still have a staff to manage applications may be open to another level of integration with a combined Fusion/Eloqua/Siebel offer, but for those SMBs already on SFDC, it is very unlikely that there would be a compelling reason to move from SaaS to an on-premise model; getting away from capital purchases, IT headcount, maintenance fees and software upgrades was the main reason for going with Salesforce.com from the beginning. Same for those who are already managing their marketing campaigns and customer communication programs using Eloqua; it is hard to take that away without some revenue risk and employee dissatisfaction.

3)      In a recent Techaisle survey, 77% of SMBs interviewed stated they were looking for vendors to reduce complexity. The type and level of integration of Eloqua into the larger Siebel suite will either make things more or less complicated depending on the approach taken by product managers to create a seamless experience.

Competitors:

4)     Oracle denies access to Eloqua’s technology to Salesforce.com, which would have been a very good fit both in terms of customer acquisition/migration and start up culture. This may well be the most important (short-term) advantage gained by Oracle. This moves Marketo, SliverPop and others up the ladder as the large independents in the space, with Hubspot and Marketo obvious next-in-line M&A targets, in a market that has seen scores of start-ups, mergers and acquisitions over the past few years.

5)     Despite a 30% premium paid by Oracle for Eloqua ($23/share over the market $17), there is already a class action suit alleging that the board should have shopped a buyer more aggressively, suggesting a $27 price as more reasonable. No comment.

6)     Over the longer term the implications are larger in a market that is moving fast, which will be influenced increasingly by Big Data, Automation and Optimization -  Enterprise capabilities to compete with the big players like IBM,  Salesforce.com and  SAP, who will be bringing competition and automation to a new level in the next few years. A recent Wikibon Post is a good example of how hardware and software are evolving to meet these emerging real time challenges. The post describes how fast the bar is rising in optimization in general and online advertising in particular:

“Many commercial Web publishers make space available on their Web pages for banner and display advertisements. Typically, when a user opens such a Web page, the browser reaches out to an online ad exchange network and requests an ad unit to serve to that user. The ad exchange broadcasts this information, often enriched with behavior data specific to the user in question, to multiple advertisers. Each advertiser compares the information against its internal ad inventory and existing ad campaigns to determine what that ad impression is "worth" to them. It then decides whether to place a bid and at what amount. Bids are returned to the ad exchange, which determines who the highest bidder is and delivers the winning advertisement.”
- Wikibon

All without noticeable lag to the user. These are the kind of industrial strength capabilities that are on the way as the market compounds at almost 130%, dominated by Mobile spending as devices grow by the hundreds of millions, as shown in this Kleiner-Perkins forecast.

Who’s Next?

So in our opinion this is a significant acquisition for Oracle, mainly because Eloqua has a strong base of satisfied users and a strong brand, and strong technology that can be applied to Oracle’s stack in the long run. The $871M price tag was not enough to prevent a lawsuit for some shareholders, but represents a sizable investment for Oracle as they strive to define the ultimate Customer-Centric, Multi-Channel Relationship Management platform in their race against the large horizontal vendors in the space (IBM, SAP, SAS, Google, Teradata).  To this end Oracle has acquired eight companies in the last two years (ATG, FatWire. Endeca, RightNow, Inquira, Vitrue, Collective Intellect, and finally with this announcement, Eloqua). The scope of what used to be called the “360ᴼ customer perspective” has evolved to include pre-sales, sales, post-sales, customer service and lifetime customer value application components, with a relentless push to automate and integrate each piece of the puzzle.

In the wake of this acquisition, an obvious question is who's next? As mentioned earlier, Marketo is an obvious choice, as are Silverpop Hubspot, Responsys, and others.  Will SFDC respond in kind or continue to focus on the lower end of the market and Social Media acquisitions? Regardless, we think 2013 will continue to see a rich market for Marketing Automation M&A activity, following two years that have seen scores of transactions in the space.

 

Many organizations are starting to think about “analytics-as-a-service” (no acronym allowed) as they struggle to cope with the problem of analyzing massive amounts of data to find patterns, extract signals from background noise and make predictions. In our discussions with CIOs and others, we are increasingly talking about leveraging the private or public cloud computing to build an analytics-as-a-service model.

The strategic goal is to harness data to drive insights and better decisions faster than competition as a core competency.  Executing this goal requires developing state-of-the-art capabilities around three facets:  algorithms, platform building blocks, and infrastructure.

Analytics is moving out of the IT function and into business — marketing, research and development, into strategy.  As a result of this shift, the focus is greater on speed-to-insight than on common or low-cost platforms.   In most IT organizations it takes anywhere from 6 weeks to 6 months to procure and configure servers.  Then another several months to load configure and test software. Not very fast for a business user who needs to churn data and test hypothesis. Hence cloud-as-a-analytics alternative is gaining traction with business users.

The “analytics-as-a-service” operating model that businesses are thinking about is already being facilitated by Amazon, Opera Solutions, eBay and others like LiquidHub.  They are anticipating the value migrating from traditional outmoded BI to an Analytics-as-a-service model.  We believe that Amazon’s analytics-as-a-service model provides a directional and aspirational target for IT organizations who want to build an on-premise equivalent.

 

Situation/Problem Summary: The Challenges of Departmental or Functional Analytics

The dominant design of analytics today is static or dependent on specific questions or dimensions. With the need for predictive analytics-driven business insights growing at ever increasing speeds, it’s clear that current departmental stove-pipe implementations are unable to meet the demands of increasingly complex KPIs, metrics and dashboards that will define the coming generation of Enterprise Performance Management. The fact that this capability will also be available to SMBs follows the trend of embedded BI and dashboards that is already sweeping the market as an integral part of SaaS applications. As we have written in the past, the move to true mobile BI can be provided as an application "bolt-ons" that work in conjunction with an existing Enterprise Applications or as pure play developed from scratch BI applications that take advantage of new technologies like HTML5. Generally, the large companies do the former through acquisition with existing technology and integration and with start-ups for the latter. Whether at the Departmental or Enterprise level, the requirements to hold down costs, minimize complexity and increase access and usability are pretty much universal, especially for SMBs, who are quickly moving away from on-premise equipment, software and services.

After years of cost cutting, organizations are looking for top-line growth again and finding that with the proliferation of front-end analytics tools and back-end BI tools, platforms and data marts, the burden/overhead of managing, maintaining and developing the “raw data to insights” value chain is growing in cost and complexity - a balance that brings SaaS and on-premise benefits together is needed.

The perennial challenge of a good BI deployment remains: it is becoming increasingly necessary to bring the disparate platforms/tools/information into a more centralized but flexible analytical architecture. Add to this the growth in volume of Big Data across all company types and the challenges accelerate.

Centralization of analytics infrastructure conflicts with the business requirement of time-to-impact, high quality and rate of user adoption - time can be more important than money if the application is strategic.  Line of Business teams need usable, adaptable, and flexible and constantly changing insights to keep up with customers.  The front-line teams care about revenue, alignment with customers and sales opportunities. So how do you bridge the two worlds and deliver the ultimate flexibility with the lowest possible cost of ownership?

The solution is Analytics-as-a-Service.

 

Emerging Operating Model:  Analytics-as-a-Service

It’s clear that sophisticated firms are moving along a trajectory of consolidating their departmental platforms into general purpose analytical platforms (either inside or outside the firewall) and then packaging them into a shared services utility.

This model is about providing a cloud computing model for analytics to anyone within or even outside an organization.  Fundamental building blocks (or enablers) like – Information Security, Data Integrity, Data and Storage Management, iPad and Mobile capabilities and other aspects – which are critical, don’t have to be designed, developed, tested again and again. More complex enablers like Operations Research, Data Mining, Machine Learning, Statistical models are also thought of as services.

Enterprise architects are migrating to “analytics-as-a-service” because they want to address three core challenges – size, speed, type – in every organization:

• The vast amount of data that needs to be processed to produce accurate and actionable results

 

• The speed at which one needs to analyze data to produce results

 

• The type of data that one analyzes - structured versus unstructured

The real value of this service bureau model lies in achieving the economies of scale and scope…the more virtual analytical apps one deploys, the better the overall scalability and higher the cost savings. With growing data volumes and dozens of virtual analytical apps, chances are that more and more of them leverage processing at different times, usage patterns and frequencies, one of the main selling points of service pooling in the first place.

 

Amazon Analytics-as-a-Service in the Cloud

Amazon.com is becoming a market leader in supporting the analytics-as-a-service concept. They are attacking this as a cloud-enabled business model innovation opportunity than an incremental BI extension.  This is a great example of value migration from outmoded methods to new architectural patterns that are better able to satisfy business’ priorities.

Amazon is aiming at firms that deal with lots and lots of data and need elastic/flexible infrastructure.  This can be domain areas like Gene Sequencing, Clickstream analysis, Sensors, Instrumentation, Logs, Cyber-Security, Fraud, Geolocation, Oil Exploration modeling, HR/workforce analytics and others. The challenge is to harness data and derive insights without spending years building complex infrastructure.

Amazon is betting that traditional enterprise “hard-coded” BI infrastructure will be unable to handle the data volume growth, data structure flexibility and data dimensionality issues.  Also even if the IT organization wants to evolve from the status quo they are hamstrung with resource constraints, talent shortage and tight budgets. Predicting infrastructure needs for emerging (and yet-to-be-defined) analytics scenarios is not trivial.

Analytics-as-a-service that supports dynamic requirements requires some serious heavy lifting and complex infrastructure. Enter the AWS cloud.  The cloud offers some interesting value 1) on demand; 2) pay-as-you-go; 3) elastic; 4) programmable; 5) abstraction; and in many cases 6) better security.

The core differentiator for Amazon is parallel efficiency - the effectiveness of distributing large amounts of workload over pools and grids of servers coupled with techniques like MapReduce and Hadoop.

Amazon has analyzed the core requirements for general analytics-as-a-service infrastructure and is providing core building blocks that include 1) scalable persistent storage like Amazon Elastic Block Store; 2) scalable storage like Amazon S3; 3) elastic on-demand resources like Amazon Elastic Compute Cloud (Amazon EC2); and 4) tools like Amazon Elastic MapReduce.  It offers choice in the database images (Amazon RDS, Oracle, MySQL, etc.)

 

How does Amazon Analytics-in-the-Cloud work?

BestBuy had a clickstream analysis problem — 3.5 billion records, 71 million unique cookies, 1.7 million targeted ads required per day. How to make sense of this data? They used a partner to implement an analytic solution on Amazon Web Services and Elastic MapReduce. Solution was a 100 node cluster on demand; processing time was reduced from 2+ days to 8 hours.

Predictive exploration of data, separating “signals from noise” is the base use case. This manifests in different problem spaces like targeted advertising / clickstream analysis; data warehousing applications; bioinformatics; financial modeling; file processing; web indexing; data mining and BI.  Amazon analytics-as-a-service is perfect for compute intensive scenarios in financial services like Credit Ratings, Fraud Models, Portfolio analysis, and VaR calculations.

The ultimate goal for Amazon in Analytics-as-a-Service is to provide unconstrained tools for unconstrained growth. What is interesting is that an architecture of mixing commercial off-the-shelf packages with core Amazon services is also possible.

 

The Power of Amazon’s Analytics-as-a-Service

So what does the future hold?  The market in predictive analytics is shifting.  It is moving from “Data-at-Rest” to “Data-in-motion” Analytics.

The service infrastructure to do “data-in-motion” analytics is pretty complicated to setup and execute.  The complexity ranges from the core (e.g., analytics and query optimization), to the practical (e.g., horizontal scaling), to the mundane (e.g., backup and recovery).  Doing all these well while insulating the end-user is where Amazon.com will be most dominant.

 

Data in motion analytics

Data “in motion” analytics is the analysis of data before it has come to rest on a hard drive or other storage medium. Due to the vast amount of data being collected today, it is often not feasible to store the data first before analyzing it. In addition, even if you have the space to store the data first, additional time is required to store and then analyze. This time delay is often not acceptable in some use cases.

 

Data at rest analytics

Due to the vast amounts of data stored, technology is needed to sift through it, make sense of it, and draw conclusions from it. Much data is stored in relational or OLAP stores. But, more data today is not stored in a structured manner. With the explosive growth of unstructured data, technology is required to provide analytics on relational, non-relational, structured, and unstructured data sources.

Now Amazon AWS is not the only show in town attempting to provide analytics-as-a-service.  Competitors like Google BigQuery, a managed data analytics service in the cloud is aimed at analyzing big sets of data… one can run query analysis on big data sets — 5 to ten terabytes — and get a response back pretty quickly, in a matter of seconds, ten to twenty seconds. That’s pretty useful when you just want a standardized self-service machine learning service. How is BigQuery used? Claritic has built an application for game developers to gather real-time insights into gaming behavior. Another firm, Crystalloids, built an application to help a resort network “analyze customer reservations, optimize marketing and maximize revenue.” (THINKstrategies’ Cloud Analytics Summit in April, Ju-kay Kwek, product manager for Google’s cloud platform).

 

Bottom-line and Takeaways

Analytics is moving from the domain of departments to the enterprise level.   As the demand for analytics grows rapidly the CIOs and IT organizations are going to be under increasing pressure to deliver.  It will be especially interesting to watch how companies that have outsourced and offshored extensively (50+%) to Infosys, TCS, IBM,  Wipro, Cognizant, Accenture, HP, CapGemini and others will adapt and leverage their partners to deliver analytics innovation.

At the enterprise level a shared utility model is the right operating model.  But given the multiple BI projects already in progress and vendor stacks in place (sunk cost and effort); it is going to be extraordinarily difficult in most large corporations to rip-and-replace.  They will instead take a conservative and incremental integrate-and-enhance-what-we-have approach which will put them at a disadvantage. Users will increasingly complain that IT is not able to deliver what innovators like Amazon Web Services are providing.

Amazon’s analytics-as-a-service platform strategy shows exactly where the enterprise analytics marketplace is moving to or needs to go. But most IT groups are going to struggle to implement this trajectory without some strong leadership support, experimentation and program management. We expect this enterprise analytics transformation trend will take a decade to play out (innovation to maturity cycle).

Shirish Netke

Announcement

Cisco has announced a new Cloud and Managed Services Program (CMSP) that integrates its currently existing Cloud Provider, Cloud Services and Managed Services Channel Programs (MSCP) into one. Besides streamlining incentives, discounts and payments for its partners, the program also aims to simplify pricing for Cisco-based cloud and managed services offerings. The program will also enable collaboration and sharing of complementary opportunities between partners through a microsite via Cisco’s partner portal. All partners are expected to transition to the CMSP by August 2013.

Techaisle Take

We believe that with one master move Cisco is strategically addressing the US$94 billion global SMB opportunity by 2016.

Techaisle’s global channel surveys have shown that Cloud, Mobility, and Managed Services Solutions together are changing the SMB channel landscape as these solutions are revolutionizing IT utilization by SMBs. The new paradigm would be the "3-in-1" Channels offering Mobility, Cloud, and Managed Services as a single offering. We first wrote about the 3-in-1 channel here. And now Virtualization is quickly becoming a potent arsenal in the SMB channel partners offerings.

Techaisle’s corresponding SMB research has consistently shown that SMBs want mostly integrated solutions to limit complexity and therefore seek partners that are capable of such deliverables but very few partners currently do so as they are all camped in either one or two solution corners and few seem to embrace a holistic solution view - and this is making SMBs unsure of overall benefits and desire to spend.

With its current announcement Cisco is removing some of the barriers by bringing channel partners serving managed services and cloud needs of SMBs under a common cluster. Since many SMBs want to obtain all services from a single provider, it is important for broad product/solution vendors to evaluate all their partners, seek and cluster partners based on where they are with regards to capabilities of delivering complete solutions and introduce programs to support development. As the dividing line between cloud and managed services is becoming thin, Cisco has just done it, that is, created a single program that should:

• Enable channels to build more dynamic and serious partner-to-partner collaboration to collectively address complementary opportunities


• Enable Cisco partners to add capabilities, such as, managed services to an existing cloud services


• Attract newer partners to join Cisco program


• Help current channel partners qualify and move up Cisco’s channel partner pyramid

The data on the right from Techaisle’s channel study (N=2851) shows that channels that serve the SMB segment are keen to offer multiple services that straddle cloud and managed services. Cisco’s new program should open up opportunity for its channel partners to offer both cloud and managed services using Cisco platforms.

If we look at the survey data at micro-level, we find that is a higher percentage of Channel Partners that are offering some type of Managed Services Solutions than they are offering Mobility Solutions or even Cloud Computing. The channels falling in the green columns will benefit immediately, those in the blue columns will find the program attractive but those within the red columns in the chart would be of immense importance.

It is clear that Managed Services has been the most important offering for Channel Partners, as they evolved from a typical value added channel to offering break-fix services and remote managed services.



The path being chosen by Channels to move from one offering to the next is strongly dependent upon their current offering. Those that are in the mobility space are moving to cloud, while those in the cloud are moving to managed services.

Understanding the channel dynamics and current offerings gives clues in the direction they will move. For those that are offering only one of the services there is a clear path to adding services. In fact Techaisle survey shows that the channels have chosen their path of selection.

Channels are also interested in offering mobility solutions, however, it is also clear that mobility has become possible due to cloud and managed services allowing employees to work from anywhere, anytime and from any device.

 

The responsibility now lies with both the channel partners and Cisco to make the program a success. However, there some other steps that Cisco needs to take as well.

• Extend the reach of its Smart Care to cover cloud based services


• Develop capabilities that not only work with Cisco's networking devices but also with client devices. Although it must be said that Cisco is addressing some of those needs through its partnerships with other vendors


• Further the agenda on not only BYOD but also just BYO


• Market the program aggressively. Channel partners are being courted and trained by many other vendors


• Use the program to establish a strong presence in the datacenter space

With the latest move, Cisco may have begun to shift the tide in its favor more decisively.

Anurag Agrawal
Techaisle