Techaisle Blog

Hortonworks is a 100 percent open source company, in direct contrast to Cloudera, and every presentation and conversation during its first ever analyst day reinforced its unwavering commitment to open source. In a very short period of time it has come a long way as a software product company with a vision “to manage the world’s data” – data-at-rest, data-in-motion, modern data applications. It wants to enable next generation data architecture by innovating the core, to be used for any delivery model and for all data.

Hortonworks has made great strides in the last couple of years – has 800+ subscription customers and plans to add 100-150 customers per quarter; has 1600 partners which it is trying to educate, mentor and support; its community connection has 3000+ members with 11,000+ weekly visitors; and is a founding member of ODPi (open ecosystem of big data).

The trio – Cloudera, Hortonworks, MapR - are in premium because they are the pioneers in the space and businesses engage with them because of their technology leadership. But short-term advantages do not count any more. By being a public company Hortonworks has declared longevity and it can no longer be judged by having a first-mover advantage. At this stage of the company it is important to design a go-to-market business model architecture that meets the demands of modern businesses. Although Hortonworks heart and comfort zone is in technology product road map it is pivoting very well to “strike conversations with business executives” to deliver the business perspectives that they need.

Hortonwoks has grand plans for technological leadership which it hopes will increase its market share, and divert most big data purchase conversation to its transparent open source subscription model. However, it will be a long, tedious and arduous effort. Hortonworks has both awareness and reach issues. A large percentage of the midmarket and lower-enterprise businesses as well as partners that Techaisle interacts with begin their big data solution selection process with either large IT vendors or smaller consulting organizations. In Techaisle’s most recent US midmarket big data & analytics adoption survey, although 30 percent of businesses are currently either piloting or implementing a big data project and another 50 percent are planning to deploy, neither Hortonworks (nor Cloudera) are top of mind big data suppliers. The top of mind suppliers are IBM, HP, Microsoft, Dell, Oracle and Accenture – in that order. A typical door-to-door selling motion of Hortonworks may not help when the share of installed base and partner ecosystem is lower than its most dominant competitor. In its defense Hortonworks quickly points out that it has no competition because it is the only open-source company. It is certainly a difficult task and Hortonworks is building its partner program to alleviate and augment reach and sales.

The average spending on big data by midmarket customers is growing. As per Techaisle’s big data adoption trends study of last two years, the average spending has jumped from US$28,900 to US$56,600, a 96 percent increase. 53 percent of midmarket big data adopters are exploring Hadoop ecosystem including analytical database and less than 1/5th are working with NoSQL databases.

One of the top gripes of the midmarket and lower-enterprise businesses is that the sales personnel of big data companies “talk about features and who has more committers”. Instead these businesses want to know & learn how their offerings solve customer problems. To this Hortonworks has a perfect and differentiated response. It has developed a cheat sheet with two different tracks (Hortonworks calls them swim lanes) – one focused on customers that are at the cutting-edge of big data adoption and analytics and the other that are just beginning their journey and are focused on transforming their data into analytics projects. And to Hortonworks credit it has generated several powerful case studies for most business problem scenarios. These scenarios are clearly outlined in the “swim lanes” cheat sheet in a bee-hive like matrix which is easy to understand, manage and translate. This is definitely a step in the right direction for sales conversations.

There is no doubt about Hortonworks technical capability. At the analyst event Hortonworks launched its connected data platform that connects data-at-rest to data-in-motion - powered by Apache NiFi, the connected data platform acts as the bridge between Hortonworks Data Platform and Hortonworks Data Flow. It fast tracks getting data into Hadoop.

Spark is the new reality and Hortonworks understands the dynamics and the pressures. Hortonworks plans to bring enterprise Spark at scale and is rolling out Apache Spark 1.6 with faster Spark streaming, dataset APIs and automatic memory tuning. Its new Apache Ambari 2.2 provides a single pane of glass for all core services, enables express upgrades to update clusters and has new integrated SmartSense technology with nearly 250 recommendations to optimize cluster performance & availability.

But challenges are plenty. Viability of open source ecosystem is based on top talent working on hard problems and the talent is migrating to Spark rather than Hadoop. Given this vulnerability Hortonworks must find ways to remain on their good side. To address the potential issues, it has begun to curate, nurture and employ committers. But Hortonworks biggest challenge will be to show thought leadership that answers questions on the direction of open source and the dynamics of open source business model.

Hadoop is still an alien term within the business (as opposed to IT) world. It has a Unix problem. Unix was the next best thing in 1990s but developers and users did not have expertise to make it mainstream. It took Unix 9-10 years to establish itself, helped generously by education from HP, IBM, and Sun. In the same vein Hortonworks has three critical challenges – 1/ sales must educate and motivate business users to embrace Hadoop keeping Hortonworks brand front-and-center, 2/ marketing must explain its ecosystem dynamics to the end-customer, 3/ devops is at the core of an enterprise development, Hortonworks must provide thought leadership in this area.

Kudos to Hortonworks for creating a visible roadmap architecture consisting of open source components - NiFi for data ingestion, Spark for transformation, Hive for queries and Zeppelin for dashboards - that when tied together can deliver end-to-end big data solutions. However, it is a palette of moving parts, which creates a decision inertia within the end-customers, as they have to understand all vulnerabilities, trade-offs and compatibility issues. When there is a closed system, all components can be managed, but in an open system the effort is dependent upon the participation and loyalty of the community and the larger ecosystem. So far, Hortonworks engineering group’s management of the dynamics of the developer community is great, in fact, creating and maintaining an ecosystem has been an enlightened philanthropy.

Hortonworks’ product evolution direction looks similar to Oracle from 20 years back – database, applications, middleware - and Hortonworks agrees. In modern ecosystem, Hortonworks success will be dependent upon how it is able to sell its projects to the community and have them contribute their free time. Just like VHS and Betamax, which gets adopted is dependent upon talent.

It is time for Hortonworks to over-play, over-announce and over-market its ecosystem dynamics. In the meantime businesses in the market for evaluating big data solutions must check out Hortonworks sandbox – an easy way to get started.

Wall Street Journal carried an article on how regulatory burdens had made community banks “too small to succeed” despite performing better than larger banks regardless of being better capitalized and having lower default rates.

The advent of cloud technologies has the potential to change WSJ’s dire prognosis.

Cloud may have first been introduced as a means of reducing CAPEX and/or overall IT costs, but today, it is viewed by small and midmarket businesses as a means of increasing business agility and of introducing capabilities that would have been cost or time-prohibitive to deploy on traditional technology. Complementary to cloud, big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether for increasing sales, improving products or detecting fraud. SMB banks are a specific segment of SMBs who can derive the benefits of customer insight while meeting their mandatory regulatory requirements.

Techaisle classifies SMB banks as those below $10B in assets and medium sized banks as those between $10-100B in assets. SMB banks below $10B in assets often called “community banks” play a very important role in the ecosystem of SMB businesses. Although FDIC, OCC and FRB have different definitions of community banks, it is important to note that these smaller banks not only accounted for nearly half of the total of about $600B outstanding small business loans at the end of 2014 but also play a disproportionately major role in the $1.8 trillion residential mortgage origination market.

Unlike large banks, SMB banks are characterized by George Bailey in “It’s a Wonderful Life”. These banks usually have keen insights on their customers based on personal relationships and carry a tremendous amount of tribal knowledge about their customers which they use to make business decisions. While this corpus of knowledge may not be codified it does make a difference in their business operations. But is that enough in today’s hyper-competitive economy where the relationship is being increasingly controlled and dictated by customers?

Then there is another question, are these smaller banks doing enough to detect fraud? High-risk businesses that have been denied services by large banks tend to move their business to smaller banks who are less equipped to analyze these risks. These smaller banks are unknowingly exposing themselves to fraud as well as compliance risk. Regulations are agnostic to bank size and equally unforgiving of SMB banks as they are of large banks. A cloud-based analytics solution may just be the recipe for success for the smaller banks. In fact, these banks are no different than midmarket businesses (or even small businesses) in their objectives of adopting big data.

Monitoring, analyzing and reporting very large volumes of data are typically the largest components of regulatory costs for SMB banks. Many often use antiquated technology and manual processes to manage their compliance requirements. Banks that are able to automate the process of managing data for regulatory requirements can have the added benefit of getting a unique view of their customers through one single technology solution.

According to Shirish Netke CEO, Amberoon, a provider of Big Data solutions for banks, “A lot of the data that is required for regulatory compliance can also be easily parlayed into getting insights on the banks customers and improving business”. Amberoon has built a banking solution for SMB banks provisioned on the IBM SoftLayer cloud.

Security & privacy (especially FFIEC requirements), traditional inhibitors of cloud adoption, are a legitimate concern for banks. After all, banks are the custodians of individual’s money, facilitators of trade and commerce and life-line of businesses. However, it may be argued that these inhibitors have already been successfully addressed by service bureaus. A very large percent of SMB banks outsource their core banking system to service providers such as Fiserv and FIS Global who have built very large scalable service bureaus with the economies of scale afforded by centralizing technology resources.

Aptly put by Noor Menai, CEO of CTBC Bank. “Outsourced technology services are nothing new in the banking industry. There is a compelling reason to use big data technologies in banks if they are available at an affordable cost in a secure manner. Cloud has the potential to provide both”.

Big data analytics in the cloud can be an execution advantage, and may even propel the SMB banks to leap ahead of larger banks on solutions that address both regulatory necessities as well as gain competitive edge from customer analytics. Historically, Siebel, an on-premise solution, was usually deployed in large enterprises and was out of reach for smaller businesses. Salesforce, a cloud solution, changed the perception, adoption, usage, affordability and provided immediate business outcomes. Today Salesforce is used by both SMBs as well as large enterprises.

Combining the benefits of cloud with the advantages of big data analytics may just be the prescription that SMB banks need for business growth (cross-selling, upselling services), meeting regulatory requirements such as KYC/AML/BSA and deep-diving into fraud detection.

One should also not forget that big data implementations require a unique combination of technical, operational and business skills to be used in a sustained manner. Needless to say, these skills are in short-supply but affordable by deep-pocketed larger banks. While some smaller banks including community banks can spend the money to experiment with big data pilots, they do not have the capacity to go through expensive iterations to get it right. While larger banks have the luxury of choosing between on-premise big data versus cloud big data, for smaller banks the choice could very well be between either doing big data on the cloud or perhaps not doing it at all. The remaining question therefore is – which big data cloud supplier will take the lead in educating, evangelizing and then executing on the needs of SMB banks.

Techaisle’s latest SMB and Channel partner research shows that Dell more than doubled its approval scores among channel partners since 2013, and improved 15% among SMB tech buyers compared to 2014. 52% of US SMBs say they like Dell, which is up from 45% in 2014 and 53% of SMB channel partners, up from 26% in 2013. Dell is still vying to acquire a seat at the enterprise CIO table but at least within SMBs and midmarket firms Dell’s impact is being felt.

Dell is in a good place. Bolstered by its decade of purposeful targeted acquisitions and thrust into the center as its competitors disintegrate and regroup. Perhaps, without the confluence of these fortuitous events Dell may have been the engine that could but did not. While it has some ways to go before it reaches its destination, Dell’s end-to-end solutions train is on the move, on the right track and making good progress. Faster, stronger, better infrastructure solutions that span from the center of IT to the edge of network can only fuel growth to a certain extent. In an industry which is vying for the mindshare of buyers, Dell has to rise above with expanded branding and general awareness initiatives, including thought leadership campaigns, and not rely exclusively on its massive sales strengths. There is some good work being done by Dr. Jai Menon, Chief Research Officer & Vice President on technology evolution such as SBDC (Software-based Data Centers), HVC (High Velocity Clouds), NVM (Non-Volatile Memory) and DLP (Data Loss Prevention). Dell is also doing a great job of leading conversations on the importance of entrepreneurship around the globe to help spur innovation, employment and economic growth. Dell acquired more patents in 2014 (20+% growth) than any year in Dell history. However, most SMB buyers are yet unaware about Dell’s full capabilities and investments in these areas and how they affect the future readiness of SMB and midmarket firms' own IT.

Let us break down some key areas of SMB IT investment and Dell’s relevance.

Mobility

Mobility is a top IT priority for 76% of global SMBs and in US alone SMBs spent US$50B on mobility in 2014 (Source: Techaisle 2015 global SMB and Midmarket Mobility Adoption Study). There is no doubt that Dell has a strong presence in the mobile device segment with its laptops (especially XPS13), and Venue tablets. Dell has chosen not to participate in the Smartphone segment and rightfully so. But question remains: How does Dell stay relevant in emerging economies such as India which have moved overwhelmingly to the mobile phone and are moving rapidly to the smartphone, where Dell is not a significant player? The answer may lie in Dell’s focus on commercial PC segment where the market is both under-penetrated and has low PC to employee density.

SMB mobility is usually defined not by devices but by the workplace where those devices and their users are. Accordingly, SMBs are not only planning to adopt mobility applications, but are also seeking mobility solutions that enable their mobile workforce - specifically solutions that provide management, security and infrastructure needed to connect mobile devices and applications into corporate IT environment. Mobility solution is Dell’s strongest suite of offerings built from various components such as Dell KACE, Dell SonicWALL, Dell Cloud Client Computing (Wyse thin clients), Dell Data Protection software and Dell Mobile as well as Desktop Workspace (Wyse vWorkspace).

However, Dell is not the first mobility solution supplier that comes to mind. A category that is in high growth mode today, which responds to a rapidly-growing SMB market need and drives high spending levels within SMB accounts is clearly attractive to a wide range of potential suppliers. Ordinarily, one would expect to find that large horizontal IT vendors like Dell with its portfolio of mobility security and mobile management offerings have staked out the high ground in a market of this type, and that channel members are acting as guides to their SMB clients. However, data from Techaisle’s SMB Mobility Adoption survey shows that SMB buyers are predominantly turning to specialized firms for mobility solutions.

Recognizing the need to be front and center Dell is investing in training its channel partners on mobility solution offerings but to be really successful Dell must define its offerings in more commonly understood categories - Mobile device management, Enterprise mobile management, Windows-as-a-service, thin clients and mobile app security.

Cloud

Cloud is no longer a trend that is discrete from mainstream IT. Techaisle’s global SMB and Midmarket Cloud Adoption trends survey data shows that cloud computing is viewed as an IT priority by 96% of US SMBs and a similar percent globally. Within the US alone, SMBs spent US$30B on cloud in 2014. Cloud is established as essential IT infrastructure for SMBs and Techaisle expects cloud momentum to continue as cloud addresses some of the key IT issues faced by SMBs.

Data shows that the larger SMB cloud trend is towards deeper use of SaaS. There is still scope for additional use of cloud infrastructure to replace and/or supplement physical back-office gear, but there is a limit to how much infrastructure is required by an SMB. Dell is a cloud infrastructure supplier with a formidable set of offerings and services which includes its converged infrastructure solutions, cloud client computing capabilities, and infrastructure management and integration solutions for cloud environments. But again, despite its investments, Dell is not the most widely recognized suppliers of converged infrastructure by SMB end-users and SMB channel partners (Sources: Techaisle SMB Converged Infrastructure Adoption Study & SMB Channel Partner Trends study). Nor is it mentioned among the top 5 IT suppliers for cloud infrastructure solutions by SMBs as per Techaisle’s recent survey.

But for those SMBs and midmarket firms that are moving rapidly to private or hybrid cloud deployments Dell combines the scale and efficiencies of its PowerEdge FX portfolio with solutions like Active Systems Manager and Dell Cloud Manager to deliver the infrastructure building blocks and management capabilities needed for private or hybrid environments. Furthermore, Dell works closely with partners, such as VMware (for EVO: RAIL) and Microsoft (for Azure) in delivering tightly integrated and engineered cloud solutions. There is tremendous merit in what Dell is doing and specific SMB segments are paying attention. As per Techaisle’s SMB attitudinal segmentation, Dell is becoming a go-to supplier of on-premise cloud infrastructure for “growth-aspiring” and “innovation-driven” SMBs and Midmarket firms.

Big Data

Techaisle’s study on SMB and Midmarket Big Data Adoption and Trends shows that 7 percent of small businesses and 20 percent of midmarket businesses are currently using Big Data solutions and that another 17 percent & 38 percent respectively is planning to adopt within the next 1-2 years. The promise of superior data-driven decision making is motivating SMBs to invest in Big Data technology. This represents a sizable opportunity considering that the segment is relatively new, it requires a certain level of IT sophistication and a history in linear investment in IT enablers to be successful. In 2014 US SMBs spent slightly over US$3B on big data. Specifically, midmarket attitude towards Big Data has transitioned from “over-hype” to must-have technology with the increase in employee size.

Dell has certainly dipped its toes into big data analytics with its acquisition of StatSoft and its Statistica advanced analytics solution. Its other two big data products Dell Kitenga and Dell Toad Data Point are incidental yet complementary to Dell’s big data solution stack. It is not out of place to mention that both Kitenga and Toad Data Point came from acquisitions. But the overarching anchors of Dell’s big data strategy are its partnerships with Cloudera & Intel (integration of Dell’s in-memory appliance with Cloudera Enterprise) and Dell’s professional services. Statistica may have one leg up on SAS due to its visualization capability and another leg up on Tableau with its statistical functionality. But it will be interesting to see where and how much of resources will Dell commit to drive its big data solution stack adoption beyond the healthcare vertical (where it has tremendous strength due to acquisition of Perot Systems). For now, most SMBs and midmarket firms are turning to Dell for their big data infrastructure platform. In a most recent set of depth interviews conducted with midmarket firms, Techaisle found that almost 9 out of 10 big data implementations were on Dell platform. Techaisle’s expectations are that, in true Dell fashion, Dell may be best positioned to commoditize big data solution and bring it out from the farmers’ market to the freezer aisle for SMBs to accelerate adoption.

Supplemental to big data, IoT is another relevant area for SMBs. Techaisle’s most recent global SMB technology adoption study shows that 52% of US midmarket firms and 18% of small businesses are either currently investing or planning to invest in IoT predominantly for security, fleet management, asset tracking and supply-chain visibility. Dell has a new IoT division and its first product is a US$500 gateway (re-purposed Wyse Thin Client) which supports Ubuntu, Wind River and Thinkworks PTC. Although one may argue that Dell is going back to its product DNA and building commoditized IoT solution but Dell may well have an advantage. By combining security from SecureWorks, analytical engine of Statistica and wrapping with Dell professional services, it may be well ahead with an end-to-end IoT solution. At least, Dell’s IoT offering is easy to understand and deploy for small and midmarket businesses.

Security and Virtualization are two other areas of importance for an SMB organization. Dell is present in both these areas. In security Dell has its own IP whereas for virtualization Dell is platform agnostic and has designed a set of blueprints that works with VMware, Citrix and Nutanix. However when the security market is growing at double digits, Dell’s software security growth in the area has been 7% (Dell does not disclose its entire security revenue details). Dell may well be suffering from a 1 vs. 1 selling as opposed to wider knowledge of Dell’s security offerings.

Final Techaisle Take

Dell has successfully put together a full set of flexible and scalable technology solution building blocks. Its sales organization is learning how to use these “blocks” successfully to build robust and future ready IT solutions for its SMB customers. Dell’s channel organization has also been focusing on equipping its channel partners with the same level of understanding. Dell has also set up cross-functional teams as Centers of Excellence that are empowered to educate and guide channel partners. These blocks may look very easy to assemble but articulation of their capabilities is very tough unless a complete picture of the end outcome is shown beforehand. And Dell has its homework assigned – demonstrate business outcomes through use cases and show thought leadership by expounding forward thinking because within the eyes of many SMBs and SMB channel partners, Dell still lags other IT suppliers on innovative and cutting edge technology front (Source: Techaisle 2015 SMB survey). That said, Dell Blueprints, for integrating piece parts into whole solutions, may just be the answer that SMBs and channel partners are looking for.

Techaisle’s quantitative study (survey of nearly 900 SMBs) on SMB & Midmarket Big Data Adoption and Trends shows that 7 percent of small businesses and 20 percent of midmarket businesses are currently using Big Data solutions and that another 17 percent & 38 percent respectively are planning to adopt within the 1-2 years. These businesses are looking at a big data solution from 3 perspectives:

“First, what are the organizational needs, second, what could be served as a solution and, third, what could be the best combination of the tools and technologies available today which will provide value add. Based on all one should decide on a solution because the Big Data space is very enormous and could be applied for any domain,” aptly quoted by CIO of a midmarket firm who has successfully implemented big data solutions in his organization.

Common findings that run through corresponding depth interviews (over 60 interviews conducted globally) conducted by Techaisle, Insights from the Trenches of SMB Big Data Implementers, are:

• PoC – more is better, timing is of essence
• Cost efficiencies of Hadoop, especially Cloudera
• Plethora of tools deployment – emergence of Spark and Flume
• On-premise only – now and the future
• Must conduct skills training and gap analysis
• Lessons learned – not to underestimate complexity but uniform voice – go for it

The promise of superior data-driven decision making is motivating 24 percent of US small businesses (1-99 employees) and 58 percent of midmarket businesses (100-999 employees) to invest in Big Data technology.

In addition, the possibility of analyzing a variety of data producing action-driven business insights is too big to ignore for midmarket businesses. This represents a sizable opportunity considering that the segment is relatively new, it requires a certain level of IT sophistication and a history in linear investment in information technology enablers to be successful.

Specifically, midmarket attitude towards big data has transitioned from “over-hype” to “must-have” technology with the increase in employee size. Only 11 percent of midmarket businesses consider big data to be an over hype suggesting that it has crossed the tipping point faster than similar sentiments for cloud adoption at its introduction. However, nearly one-fourth of lower mid-market businesses still consider it to be over-hyped yet 29 percent think that it will be an important part of their business decision making process.

Nevertheless, SMBs face many challenges in implementing big data solutions.

There are many different tactical objectives for deploying big data projects and SMBs are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations, and improved customer service.

CRM solutions had first established the analytics for analyzing customer data but 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 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 for generating sales, improving products or detecting fraud. It is therefore not surprising that globally SMBs and midmarket 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.