iot-adoption_paasmer

IoT Adoption – Ambitious growth with Formidable Technical Challenge – How PAASMER fits in?

A recent Gartner survey provided key insights and recommendations on IoT adoption. We recently did an exercise to map these key findings and recommendations to our IoT Platform of A Service – PAASMER.  We have highlighted the points significantly addressed by PAASMER in block letters below. PAASMER – Being a Gateway/Cloud centric architecture addresses the highlighted area in comprehensive manner by design.

As stated in PAASMER press coverage on Raconteur online – PAASMER scores extremely high over other existing architectures by being most flexible and scalable.

Gartner Key Findings

  • The number of IoT projects per organization is surprisingly high; companies that have implemented IoT have, on average, 6.8 different IoT projects, and the number of projects is expected to rise to 11.5 within three years.
  • Heavy (asset-oriented) industries are focused on internal benefits (for example, asset optimization) and plan to implement about twice as many projects (16.3 versus 8.9) as companies in light (service-oriented) industries, which are more focused on external benefits (for example, new revenue sources).
  • Fifty-one percent and 43% of survey respondents identified cybersecurity and integration, respectively, as their top two technical challenges for IoT projects.
  • More than one-third (38%) of respondents that have already implemented or are planning to implement IoT are planning to use an IoT platform for their next IoT project.

Gartner Recommendations

CIOs and IT leaders should:

  • Treat IoT project proliferation as a call to action: Consider the role of IoT in your company, and build plans to leverage it by year-end 2016. Expect these “living plans” to evolve over time.
  • Incorporate IoT into your enterprise architecture. Invest in integration middleware either for IoT/OT integration with MES or other applications in heavy industries, or for IoT/IT integration with core enterprise applications, such as ERP, in light industries.
  • Develop a comprehensive cybersecurity strategy early in IoT project planning to mitigate post deployment challenges.

Companies that do not yet plan or do not yet know whether they will use an IoT platform for their IoT project should learn more about the maturity and potential benefits of this middleware.

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bi & A

Key Drivers of Business Intelligence & Analytics market

ManagementTeamMouli1

Chandramouli Srinivasan

The overall BI and analytics market segment continues to expand and is expected to sustain its 2014 growth rate of 5.8% (adjusted for constant currency) through 2019 — as reflected in Gartner’s current estimate of the compound annual growth rate for the sector. However, this lower rate of growth reflects a market in transition, with changing buying patterns and requirements. Purchasing decisions continue to move from IT leaders to line-of-business executives and users who want more agility and more flexible personalized options — making the land-and-expand model the new norm. This is in stark contrast to the large, enterprise-scale deals that fueled double-digit growth at a time when IT had larger budgets and wielded much more influence in buying decisions.

The primary drivers of new growth in this rapidly evolving market are being influenced by the following dynamics:

  • New vendors continue to emerge, offering innovative products to the market for buyers to consider. During the next several years, buyers will benefit from the attention that vendors are giving to the BI and analytics market and will have ample opportunity to invest in the innovative product offerings that are brought to market. The downside of having a plethora of innovative products to pilot and vendors to engage in POCs with, is the tendency for organizations to incur technical debt over time — as multiple stand-alone solutions that demonstrate business value quickly (and hastily) turn into production deployments without adequate attention being paid to design, implementation and support.
  • The increased need for governance will serve as the catalyst for renewed IT engagement as business-user-led deployments expand. When the market shift first began, business users felt empowered to circumvent IT and autonomously purchase and begin using any product that addressed the gaps in their enterprise BI program.
  • Market awareness and adoption of smart data discovery will extend data discovery to a wider range of users, increasing the reach and impact of analytics. These emerging capabilities facilitate discovery of hidden patterns in large, complex and increasingly multi-structured datasets, without building models or writing algorithms or queries.
  • The need for organizations to integrate and derive insight from a growing number of multi-structured data sources will drive innovation in smart self-service data preparation and smart data discovery. Organizations will require sophisticated software capabilities that automate the ingestion, inference, enrichment and creation of search indexes when accessing new data sources.
  • Search-based data discovery enabled by natural-language query will extend the reach of analytics to more users. As BI and analytics platforms increasingly support natural-language query, allowing nontechnical users to analyze data by asking questions in a conversational way, new users are more likely to engage with and leverage analytics.
  • Marketplaces will expand and mature, creating new opportunities for organizations to buy and sell analytic capabilities. The availability of an active marketplace where buyers and sellers converge to exchange analytic applications, aggregated data sources, custom visualizations and algorithms is likely to generate increased interest in the BI and analytics space and to fuel its future growth.
  • Organizations will need to support real-time events and streaming data capture in support of IoT use cases. In order for organizations to prepare for the volume of data that is generated by devices, sensors and people in a connected world, organizations will have to make new investments in products that are designed to capture and process this type of data.

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Cloud Services Opportunity

Cloud Services Opportunity – Prime Time for Cloud Service Players to different and win the market place

ManagementTeamMouli1

Chandramouli Srinivasan

I was talking to an analyst about cloud services business opportunity for SMB Players like MoboDexter. A few key points emerged that were really interesting and concurred with our understanding as MoboDexter’s Cloud Services Offering is already into this space and working with players like Harman Connected Services. Sharing the key points from this discussion here.
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JAR:Load

JAR:Load – Cloud Based Web Load Testing Software

ManagementTeamMouli1

Chandramouli Srinivasan

I am Happy to announce that MoboDexter Inc. has signed a partnership agreement with JAR Technologies, U.K. to sell their Cloud Based Loading Testing solution called JAR:Load. As part of this agreement, MoboDexter has secured an exclusive pricing deal that can be leveraged by any prospect who wants to purchase JAR: Load through MoboDexter. I want to talk about the reason why I felt this is a compelling tool in the market in comparison to its competitor products.

JAR:Load – Stand Out Features

  • JAR: Load is the only enterprise load testing product, delivered from the cloud, that uses real web browsers to simulate load. If you run ANY type of JavaScript (jQuery, GWT, AngularJS, Ember, etc.) on your web-site then you can’t rely on “other” load testers who just record HTTP transactions – they will miss all your dynamic AJAX operations!
  • (more…)

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IOT and Big Data

A proof of real Excitement around IOT and Big Data in the B2B space

ManagementTeamMouli1

Chandramouli Srinivasan

I got to meet my clients, prospective clients and partners in India this December 2015 and had an opportunity to have an engaged discussion with them.

Since many of our clients/prospective clients are in service delivery space the discussion topics ranged from

1) Challenges facing the businesses in IOT & Big Data space.
2) Expectation on higher Business Value creation and higher ROI.
3) Proposal for better service delivery ownership models.

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