Techaisle Blog

Various organizations define Big Data differently. Some use “petabytes of data” as a benchmark to isolate big data from other normalized and structured data sets that exist within an organization. However, this measure quickly boxes big data analytics into the large enterprise market segment. Small and mid-market businesses certainly do not have this extent of data but Big Data still relevant for them. In fact Big Data solutions are more relevant for Small and Mid-Market businesses. However, it will take some creativity on the part of solution providers to make Big Data accessible, easy to use and comprehend for segment that constitutes 97 percent of global businesses.

Cloud computing started as an enterprise play, however, it was quickly discovered that SMBs will be the more relevant target segment with a faster path to adoption. Similarly, as Virtualization market started getting fully penetrated within the enterprises, vendors shifted their focus to the SMBs with some very creative solutions. As far as big data is concerned SMBs are starting to show interest and even adoption. However, there is a stark difference in approaches between mid-market businesses and small businesses. While mid-market businesses are experimenting with bespoke solutions, small businesses are gravitating towards a multi-tenant, aggregated and federated big data solution that has a mix of publicly available data and their own internal data.

It is expected that in year 2016, global SMBs would spend US$1.6 Billion on big data solutions exhibiting a growth rate that is faster than what was exhibited by cloud computing solutions. Cumulatively between now and end of 2016, SMBs itself would have shelled out US$3.9 billion on big data solutions. This spending includes hardware, software and services.

So why are many big data solution providers ignoring SMBs? Simply put, because of perceived complexity and inability to create bite-sized messaging that directly address SMBs pain-points. But they should not forget that business intelligence has now become one of the fastest solutions to be adopted by SMBs. If done right, Big data address three key pain points of SMBs: Increase sales, Efficient operations, Improve Customer service.

Promise of Superior Decision Making

Let us take Techaisle’s recent global mid-market businesses’ Big Data Adoption & Trends study which clearly shows that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to either invest in or investigate Big Data technology. Out of these, 18 percent of mid-market businesses are actively investing in big data related projects. The possibilities of analyzing a variety of data sources, producing action-driven business insights is too big to ignore for these businesses.

Similar to cloud, the attitude towards Big Data is transitioning from “Over-Hype” to “Must-Have” technology with the size of business. Even within the businesses that consider big data to be over-hyped, 29 percent think that it will be an important part of their business decision making process in the future.

Extracting Business Perspectives

Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results.  Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.

CRM solutions had first established the analytics for analyzing customer data. However, the data was mostly two-way transactional data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. IT vendors and mid-market businesses figured out the need to analyze the data and combine it with transactional information.

However, everything changed with the onset of social media, blogs, forums, wikis and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking.

Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether be for generating sales, improving products or detecting fraud.

It is therefore not surprising that global mid-market businesses are turning towards big data analytics to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, voicemails.

Leap of Faith or Solution Readiness

Analyzing data from diverse sources leads a mid-market business to naturally consider linking structured and unstructured data. This also drives them to evaluate and select the technology that can be used for simplified implementation. Simplified implementation is important because mid-market businesses do not yet have in-house capabilities to analyze unstructured data and those that have them consider the capabilities at best rudimentary.

Big data therefore is a major leap of faith for mid-market businesses resulting in treating big data analytics projects usually as separate to the existing analytics within the business. More aggressive adopters are planning to use big data analytics along with other analytics in a coordinated manner so that one does not become an inhibitor for the other.

In recent years technology and technology options have evolved extremely rapidly for an average business to understand, evaluate, purchase and implement. The complexity gets further exacerbated with lack of experience, lack of skilled manpower and innate difficulty in identifying external consultants that would be the most right fit for their business objectives and budget availability.

In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment. Our study shows that mid-market businesses typically started their big data journey in one of four ways. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.

SMBs as the Path to Big Data Simplicity

The global SMB spend on big-data related deployments will cross US$1.0 billion in 2013 which is a 32 percent increase from 2012. SMBs are still experimenting to see if big data analytics can provide newer insights into their operations and better knowledge about their customers. It is still very early days for small and mid-market businesses to fully embrace big data but they are planting the seeds in terms of re-architecting their IT infrastructure to plan for the future. But we believe that SMBs may very well race ahead of enterprises with their deployments as technology becomes simpler and consultants become experienced.

 

Techaisle’s global mid-market businesses’ Big Data Adoption & Trends study shows that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to either invest in or investigate Big Data technology. Out of these, 18 percent of mid-market businesses are actively investing in big data related projects. The possibilities of analyzing a variety of data sources, producing action-driven business insights is too big to ignore for mid-market businesses.

Big Data requires a certain level of IT sophistication and a history in the linear investment in Information Technology enablers to be successfully. While these factors predispose larger accounts to Big Data, the competitive imperative to understand customers, innovate products and improve operational efficiencies has already started to reach down to the mid-Market, forcing a search for how to leverage primary and secondary data that is generated by the business.

The current and planned investment represents a sizable opportunity considering that the segment is relatively new and requires a certain level of IT sophistication and a history in linear investment in Information Technology enablers to be successful. North America has both the largest market and the highest level of investment in Big Data overall in SMB and mid-market segments. Mid-Market attitude towards Big Data transitions from “Over-Hype” to “Must-Have” technology with the increase in employee size. However, nearly one-fourth of lower mid-market businesses consider big data to be over-hyped and yet 29 percent think that it will be an important part of their business decision making process in the future.

Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results.  Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.

In addition to understanding customers, mid-market businesses are also considering big data analytics as an important initiative to help them improve operational efficiencies.

Techaisle’s study shows that there are many different tactical objectives for deploying big data projects but the top among them are sentiment monitoring, generating new revenue streams & improving predictive analytics. It must also be said that businesses have figured out that there is a lot of publicly available data which could also be analyzed to their advantage.

The mid-market businesses actively investing in big data technologies are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations and improved customer service. These objectives differ slightly by different geographic regions. As the growth rates continue to lag in mature economies, the pressure to increase revenue grows resulting in developing robust analysis and extracting insights from all sales and customer data including transactions.

When specifically asked about preferred deployment choice in terms of on-premise vs. cloud, mid-market businesses are unsure as they are still navigating through their technology options. However, Hadoop dominates as the preferred platform but confusion exists.

In terms of analytics skill-set and long-term vision, the potential of linking structured and unstructured data sources to create new business insights is being considered very useful but at the same time mid-market businesses are not really prepared for it. In fact one-third of mid-market businesses agree that linking structured and unstructured data would be very useful for big data analytics but over 70 percent mention that they have either none or very limited capabilities of analyzing unstructured data. This is where they are turning to external help for guidance.

Needless to say, survey reveals that big data deployment is posing tremendous challenges. Technology confusion, lack of skilled resources and potential unclean data are being considered as the biggest roadblocks for big data project implementations. Big data technology and its far-reaching capabilities are being viewed by mid-market businesses as very complex resulting in very steep learning curves.

In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.

Detailed Global Mid-Market Big Data Adoption and Trends report is available for purchase. Details are given here.

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.