“Loom is applying artificial intelligence and machine learning into the entire log analysis process, from start to finish and at the end you will get a human touch,” explained Sabo Taylor Diab, Vice President, Marketing at Loom Systems, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Monthly Archives: June 2017
[video] IT Self-Service Portals in a Continuous Delivery World | @CloudExpo @DellEMC #CD #Cloud #DevOps
What’s the role of an IT self-service portal when you get to continuous delivery and Infrastructure as Code? This general session showed how to create the continuous delivery culture and eight accelerators for leading the change.
Don Demcsak is a DevOps and Cloud Native Modernization Principal for Dell EMC based out of New Jersey. He is a former, long time, Microsoft Most Valuable Professional, specializing in building and architecting Application Delivery Pipelines for hybrid legacy, and cloud native applications.
RingCentral leads cloud business communication vendor race, says Synergy
RingCentral leads the way for the cloud business communications market with the overall landscape growing at a considerable clip, according to the latest note from Synergy Research.
The market is growing at an annualised rate of 23% driven by strong adoption of unified communications as a service (UCaaS), according to the research. The total cloud communication market is generating revenues in excess of $2 billion (£1.58bn) per year.
Synergy puts the market into three buckets; UCaaS retail being demonstrably the largest, followed by cloud comms and UCaaS wholesale. However, the later has a much quicker growth rate.
For RingCentral, presence as a market leader in both the former and latter are a boon – and the company pushed out an agreeable blog from CEO Vlad Shmunis with regard to the news.
“As we look ahead, we are excited about the market opportunity for cloud communications as enterprise customers empower their global and distributed workforce to work anywhere, any time, and on any device,” Shmunis wrote. “This market transition will fuel our growth to $1bn by 2020.”
“UCaaS continues to be a force for change within the business communications market,” said Jeremy Duke, Synergy Research founder and chief analyst. “Major barriers to cloud adoption are now almost a thing of the past and consequently we are seeing continued erosion of on-premises PBX-based systems. Clearly these trends will continue over the next few years.”
Other leading players in the market include 8×8, Mitel, and ShoreTel, Synergy added. According to Gartner’s Magic Quadrant for UCaaS, released in August last year, 8×8, BT, Fuze, RingCentral, and West Unified Communications found a place in the winner’s enclosure.
Adobe’s Results Prove that Cloud is the Way Forward
Adobe Systems Inc has reported another incredible quarter that beat analyst’s expectations on both profits and revenue.
Adobe has announced that revenue from its digital media business is $1.21 billion, which is almost four billion more than what analysts were expecting. Overall, it’s revenue saw a 27 percent jump as it touched $1.77 billion during this quarter. Analysts were predicting a revenue of only $1.73 billion. Also, profit per share was $1.02 per share as against the expectation of 95 cents per share.
Adobe also raised its forecast to a growth of 23 percent as against the expectation of 22 percent.
Creative Cloud is the flagship product of Adobe and it’s also the one that’s seen one of the highest demands over the last few quarters.
According to company reports, there are over nine million members in its online community, thanks to the super popular Photoshop and Flash. In fact, it is believed that there two products helped Creative Cloud as a whole to cross the $1 billion mark during the last quarter. Since then, there has been no looking back. In this quarter, Creative Cloud and the Digitial Media Annualized Recurring Revenue accounted for $4.56 billion, as against the analysts expectations of $4.54 billion.
Undoubtedly, the share price of Adobe went up by four percent to reach a record level of $146 per share.
Much of this success can be attributed to the switch that Adobe made in 2012. Led by its CEO, Shantanu Narayen, this company switched to a cloud-based model to move many of its traditional products to the cloud. Though the CEO and the management were met with stiff resistance from investors, this strategy has paid well, as is evident from the strong results that Adobe has been churning quarter after quarter.
The company has even been making some acquisitions to strengthen its portfolio and to move deeper into cloud-based services. Late last year, it acquired a company called TubeMogul for $500 million. This is a brand advertising company that adds to Adobe’s creative products, thereby providing a richer experience and greater value for its customers.
Besides acquisitions, it has also been striking lucrative partnerships to promote its products and to continue to expand its customer base. An example of this strategy is the partnership it struck with Microsoft to sell more of its business marketing products.
All these different tactics have paid off well for the company and it sure has a happy bunch of investors today. This is evident from the meteoric rise of its shares over the last few years. A quick look shows that Adobe’s share price has risen about 350 percent over the last five years and touched new levels after the results were announced on Tuesday evening.
With such a positive outlook and a clear strategic direction, Adobe exudes a lot of confidence about its future. Investors, analysts, employees and all other stakeholders like to see such exuberance, and this is partly why we can say that the performance of the company as well as its share prices are going to go through the roof in the coming months.
The post Adobe’s Results Prove that Cloud is the Way Forward appeared first on Cloud News Daily.
Adobe’s Results Prove that Cloud is the Way Forward
Adobe Systems Inc has reported another incredible quarter that beat analyst’s expectations on both profits and revenue.
Adobe has announced that revenue from its digital media business is $1.21 billion, which is almost four billion more than what analysts were expecting. Overall, it’s revenue saw a 27 percent jump as it touched $1.77 billion during this quarter. Analysts were predicting a revenue of only $1.73 billion. Also, profit per share was $1.02 per share as against the expectation of 95 cents per share.
Adobe also raised its forecast to a growth of 23 percent as against the expectation of 22 percent.
Creative Cloud is the flagship product of Adobe and it’s also the one that’s seen one of the highest demands over the last few quarters.
According to company reports, there are over nine million members in its online community, thanks to the super popular Photoshop and Flash. In fact, it is believed that there two products helped Creative Cloud as a whole to cross the $1 billion mark during the last quarter. Since then, there has been no looking back. In this quarter, Creative Cloud and the Digitial Media Annualized Recurring Revenue accounted for $4.56 billion, as against the analysts expectations of $4.54 billion.
Undoubtedly, the share price of Adobe went up by four percent to reach a record level of $146 per share.
Much of this success can be attributed to the switch that Adobe made in 2012. Led by its CEO, Shantanu Narayen, this company switched to a cloud-based model to move many of its traditional products to the cloud. Though the CEO and the management were met with stiff resistance from investors, this strategy has paid well, as is evident from the strong results that Adobe has been churning quarter after quarter.
The company has even been making some acquisitions to strengthen its portfolio and to move deeper into cloud-based services. Late last year, it acquired a company called TubeMogul for $500 million. This is a brand advertising company that adds to Adobe’s creative products, thereby providing a richer experience and greater value for its customers.
Besides acquisitions, it has also been striking lucrative partnerships to promote its products and to continue to expand its customer base. An example of this strategy is the partnership it struck with Microsoft to sell more of its business marketing products.
All these different tactics have paid off well for the company and it sure has a happy bunch of investors today. This is evident from the meteoric rise of its shares over the last few years. A quick look shows that Adobe’s share price has risen about 350 percent over the last five years and touched new levels after the results were announced on Tuesday evening.
With such a positive outlook and a clear strategic direction, Adobe exudes a lot of confidence about its future. Investors, analysts, employees and all other stakeholders like to see such exuberance, and this is partly why we can say that the performance of the company as well as its share prices are going to go through the roof in the coming months.
The post Adobe’s Results Prove that Cloud is the Way Forward appeared first on Cloud News Daily.
How artificial intelligence is revolutionising enterprise software in 2017
- 81% of IT leaders are currently investing in or planning to invest in Artificial Intelligence (AI).
- Cowen predicts AI will drive user productivity to materially higher levels, with Microsoft at the forefront.
- Digital Marketing/Marketing Automation, Salesforce Automation (CRM) and Data Analytics are the top three areas ripe for AI/ML adoption.
- According to angel.co, there are 2,200+ Artificial Intelligence startups, and well over 50% have emerged in just the last two years.
- Cowen sees Salesforce ($CRM), Adobe ($ADBE) and ServiceNow ($NOW) as well-positioned to deliver and monetize new AI-based application services.
These and many other fascinating insights are from the Cowen and Company Multi-Sector Equity Research study, Artificial Intelligence: Entering A Golden Age For Data Science (142 pp., PDF, client access reqd).
The study is based on interviews with 146 leading AI researchers, entrepreneurs and VC executives globally who are involved in the field of artificial intelligence and related technologies. Please see the Appendix of the study for a thorough overview of the methodology. This study isn’t representative of global AI, data engineering and machine learning (ML) adoption trends. It does, however, provide a glimpse into the current and future direction of AI, data engineering, and machine learning.
Cowen finds the market is still nascent, with CIOs eager to invest in new AI-related initiatives. Time-to-market, customer messaging, product positioning and the value proposition of AI solutions will be critical factors for winning over new project investments.
Key takeaways from the study include the following:
Digital marketing/marketing automation, Salesforce automation (CRM) and data analytics are the top three areas ripe for AI/ML adoption
Customer self-service, enterprise resource planning (ERP), human resource management (HRM) and eCommerce are additional areas that have upside potential for AI/ML adoption. The following graphic provides an overview of the areas in software that Cowen found the greater potential for AI/ML investment.
81% of IT leaders are currently investing in or planning to invest in artificial intelligence (AI)
Based on the study, CIOs have a new mandate to integrate AI into IT technology stacks. The study found that 43% are evaluating and doing a Proof of Concept (POC) and 38% are already live and planning to invest more. The following graphic provides an overview of company readiness for machine learning and AI projects.
Market forecasts vary, but all consistently predict explosive growth
IDC predicts that the Cognitive Systems and AI market (including hardware & services) will grow from $8B in 2016 to $47B in 2020, attaining a Compound Annual Growth Rate (CAGR) of 55%. This forecast includes $18B in software applications, $5B in software platforms, and $24B in services and hardware. IBM claims that cognitive computing is a $2T market, including $200B in healthcare/life sciences alone. Tractica forecasts direct and indirect applications of AI software to grow from $1.4B in 2016 to $59.8B by 2025, a 52% CAGR.
According to CBInsights, the number of financing transactions to AI startups increased 10x over the last six years, from 67 in 2011 to 698 in 2016
Accenture states that the total number of AI start-ups has increased 20-fold since 2011. The top verticals include fintech, healthcare, transportation and retail/eCommerce. The following graphic provides an overview of the AI annual funding history from 2011 to 2016.
Algorithmic trading, image recognition/tagging, and patient data processing are predicted to be the top AI uses cases by 2025
Tractica forecasts predictive maintenance and content distribution on social media will be the fourth and fifth highest revenue producing AI uses cases over the next eight years. The following graphic compares the top 10 uses cases by projected global revenue.
Machine learning is predicted to generate the most revenue and is attracting the most venture capital investment in all areas of AI
Venture Scanner found that ML raised $3.5B to date (from 400+ companies), far ahead of the next category, natural language processing, which has seen just over $1Bn raised to date (from 200+ companies). Venture Scanner believes that machine learning applications and machine learning platforms are two relatively early stage markets that stand to have some of the greatest market disruptions.
Cowen predicts that an Intelligent App Stack will gain rapid adoption in enterprises as IT departments shift from system-of-record to system-of-intelligence apps, platforms, and priorities
The future of enterprise software is being defined by increasingly intelligent applications today, and this will accelerate in the future. Cowen predicts it will be commonplace for enterprise apps to have machine learning algorithms that can provide predictive insights across a broad base of scenarios encompassing a company’s entire value chain. The potential exists for enterprise apps to change selling and buying behavior, tailoring specific responses based on real-time data to optimize discounting, pricing, proposal and quoting decisions.
Other forecasts
- According to angel.co, there are 2,200+ artificial intelligence startups, and well over 50% have emerged in just the last two years. Machine learning-based applications and deep learning neural networks are experiencing the largest and widest amount of investment attention in the enterprise.
- Accenture leverages machine learning in 40% of active Analytics engagements, and nearly 80% of proposed analytics opportunities today. Cowen found that Accenture’s view is that they are in the early stages of AI technology adoption with their enterprise clients. Accenture sees the AI market growing exponentially, reaching $400B in spending by 2020. Their customers have moved on from piloting and testing AI to reinventing their business strategies and models.
How artificial intelligence is revolutionising enterprise software in 2017
- 81% of IT leaders are currently investing in or planning to invest in Artificial Intelligence (AI).
- Cowen predicts AI will drive user productivity to materially higher levels, with Microsoft at the forefront.
- Digital Marketing/Marketing Automation, Salesforce Automation (CRM) and Data Analytics are the top three areas ripe for AI/ML adoption.
- According to angel.co, there are 2,200+ Artificial Intelligence startups, and well over 50% have emerged in just the last two years.
- Cowen sees Salesforce ($CRM), Adobe ($ADBE) and ServiceNow ($NOW) as well-positioned to deliver and monetize new AI-based application services.
These and many other fascinating insights are from the Cowen and Company Multi-Sector Equity Research study, Artificial Intelligence: Entering A Golden Age For Data Science (142 pp., PDF, client access reqd).
The study is based on interviews with 146 leading AI researchers, entrepreneurs and VC executives globally who are involved in the field of artificial intelligence and related technologies. Please see the Appendix of the study for a thorough overview of the methodology. This study isn’t representative of global AI, data engineering and machine learning (ML) adoption trends. It does, however, provide a glimpse into the current and future direction of AI, data engineering, and machine learning.
Cowen finds the market is still nascent, with CIOs eager to invest in new AI-related initiatives. Time-to-market, customer messaging, product positioning and the value proposition of AI solutions will be critical factors for winning over new project investments.
Key takeaways from the study include the following:
Digital marketing/marketing automation, Salesforce automation (CRM) and data analytics are the top three areas ripe for AI/ML adoption
Customer self-service, enterprise resource planning (ERP), human resource management (HRM) and eCommerce are additional areas that have upside potential for AI/ML adoption. The following graphic provides an overview of the areas in software that Cowen found the greater potential for AI/ML investment.
81% of IT leaders are currently investing in or planning to invest in artificial intelligence (AI)
Based on the study, CIOs have a new mandate to integrate AI into IT technology stacks. The study found that 43% are evaluating and doing a Proof of Concept (POC) and 38% are already live and planning to invest more. The following graphic provides an overview of company readiness for machine learning and AI projects.
Market forecasts vary, but all consistently predict explosive growth
IDC predicts that the Cognitive Systems and AI market (including hardware & services) will grow from $8B in 2016 to $47B in 2020, attaining a Compound Annual Growth Rate (CAGR) of 55%. This forecast includes $18B in software applications, $5B in software platforms, and $24B in services and hardware. IBM claims that cognitive computing is a $2T market, including $200B in healthcare/life sciences alone. Tractica forecasts direct and indirect applications of AI software to grow from $1.4B in 2016 to $59.8B by 2025, a 52% CAGR.
According to CBInsights, the number of financing transactions to AI startups increased 10x over the last six years, from 67 in 2011 to 698 in 2016
Accenture states that the total number of AI start-ups has increased 20-fold since 2011. The top verticals include fintech, healthcare, transportation and retail/eCommerce. The following graphic provides an overview of the AI annual funding history from 2011 to 2016.
Algorithmic trading, image recognition/tagging, and patient data processing are predicted to be the top AI uses cases by 2025
Tractica forecasts predictive maintenance and content distribution on social media will be the fourth and fifth highest revenue producing AI uses cases over the next eight years. The following graphic compares the top 10 uses cases by projected global revenue.
Machine learning is predicted to generate the most revenue and is attracting the most venture capital investment in all areas of AI
Venture Scanner found that ML raised $3.5B to date (from 400+ companies), far ahead of the next category, natural language processing, which has seen just over $1Bn raised to date (from 200+ companies). Venture Scanner believes that machine learning applications and machine learning platforms are two relatively early stage markets that stand to have some of the greatest market disruptions.
Cowen predicts that an Intelligent App Stack will gain rapid adoption in enterprises as IT departments shift from system-of-record to system-of-intelligence apps, platforms, and priorities
The future of enterprise software is being defined by increasingly intelligent applications today, and this will accelerate in the future. Cowen predicts it will be commonplace for enterprise apps to have machine learning algorithms that can provide predictive insights across a broad base of scenarios encompassing a company’s entire value chain. The potential exists for enterprise apps to change selling and buying behavior, tailoring specific responses based on real-time data to optimize discounting, pricing, proposal and quoting decisions.
Other forecasts
- According to angel.co, there are 2,200+ artificial intelligence startups, and well over 50% have emerged in just the last two years. Machine learning-based applications and deep learning neural networks are experiencing the largest and widest amount of investment attention in the enterprise.
- Accenture leverages machine learning in 40% of active Analytics engagements, and nearly 80% of proposed analytics opportunities today. Cowen found that Accenture’s view is that they are in the early stages of AI technology adoption with their enterprise clients. Accenture sees the AI market growing exponentially, reaching $400B in spending by 2020. Their customers have moved on from piloting and testing AI to reinventing their business strategies and models.
When to hire software testers in your organisation
Software testers are often viewed as the “last mile” investment in a tech startup. A young, early-stage software company is undeniably focused on feature development that will drive sales. There is real pressure to develop the product quickly and spin out new features to beat the competition, especially if you have outside investors tapping their fingers.
Before long, things can take off and you’ve got a couple dozen developers churning out code. Suddenly, you aren’t prepared when quality issues creep into the equation, and it becomes a process just to find out who may have written the suspect code. Existing customers start to ramp up their complaints and calls into the help desk due to bugs and application errors: that’s not a trend you want to continue. You may find your business is losing customers as fast as it’s acquiring new ones, bringing growth to a standstill.
When over-investment in development is the root of the problem, the answer is not to hire more or better developers. It’s time to start adding testers. If you have waited too long, as many well-meaning companies have, you are now stuck playing a game of catch-up. It’s difficult to integrate these testers into your company: developers may think they can do it all and senior management sees these new testers as a bottleneck generating unnecessary costs. The testers are already behind on their work from day one. So, what to do if your lean startup wants to succeed in the market yet also values high-quality products?
The first piece of advice is to be more proactive about QA. Don’t wait until you have 30 or more developers to hire dedicated testers. In fact, a company that doesn’t see the need to scale up to that many developers might hire testers soon after the core development team is in place.
There’s no right answer, but here are some factors to consider when determining the optimal timing for hiring testers:
- An established or regulated business typically hires one tester for every two to three developers when at full scale (more than 500 developers)
- For a startup with 20 developers, it’s time to get in place at least one person dedicated primarily to testing/quality
- Consider the risk of revenue without quality checks. A startup can often grow a $6-$10 million-dollar revenue stream in 3-4 years, but with no testers, it can all be lost with one major bug or outage. Savvy investors have little tolerance for poor customer retention and unhappy customers
- How many testers you will need depends upon the development culture in place. If developers are testing savvy and located in near proximity to the business staff, they will be in a better position to take on some of the testing load
- Conversely, a company with a large, outsourced development team which has little interaction with business staff at headquarters won’t have adequate institutional knowledge to test the application adequately for end user needs. There is clearly a need in these cases to hire some dedicated testers early and ensure they have a good line of communication with the business
When to hire software testers in your organisation
Software testers are often viewed as the “last mile” investment in a tech startup. A young, early-stage software company is undeniably focused on feature development that will drive sales. There is real pressure to develop the product quickly and spin out new features to beat the competition, especially if you have outside investors tapping their fingers.
Before long, things can take off and you’ve got a couple dozen developers churning out code. Suddenly, you aren’t prepared when quality issues creep into the equation, and it becomes a process just to find out who may have written the suspect code. Existing customers start to ramp up their complaints and calls into the help desk due to bugs and application errors: that’s not a trend you want to continue. You may find your business is losing customers as fast as it’s acquiring new ones, bringing growth to a standstill.
When over-investment in development is the root of the problem, the answer is not to hire more or better developers. It’s time to start adding testers. If you have waited too long, as many well-meaning companies have, you are now stuck playing a game of catch-up. It’s difficult to integrate these testers into your company: developers may think they can do it all and senior management sees these new testers as a bottleneck generating unnecessary costs. The testers are already behind on their work from day one. So, what to do if your lean startup wants to succeed in the market yet also values high-quality products?
The first piece of advice is to be more proactive about QA. Don’t wait until you have 30 or more developers to hire dedicated testers. In fact, a company that doesn’t see the need to scale up to that many developers might hire testers soon after the core development team is in place.
There’s no right answer, but here are some factors to consider when determining the optimal timing for hiring testers:
- An established or regulated business typically hires one tester for every two to three developers when at full scale (more than 500 developers)
- For a startup with 20 developers, it’s time to get in place at least one person dedicated primarily to testing/quality
- Consider the risk of revenue without quality checks. A startup can often grow a $6-$10 million-dollar revenue stream in 3-4 years, but with no testers, it can all be lost with one major bug or outage. Savvy investors have little tolerance for poor customer retention and unhappy customers
- How many testers you will need depends upon the development culture in place. If developers are testing savvy and located in near proximity to the business staff, they will be in a better position to take on some of the testing load
- Conversely, a company with a large, outsourced development team which has little interaction with business staff at headquarters won’t have adequate institutional knowledge to test the application adequately for end user needs. There is clearly a need in these cases to hire some dedicated testers early and ensure they have a good line of communication with the business
How to Sponsor @DevOpsSummit | #AI #DX #DevOps #Serverless #Monitoring
DevOps at Cloud Expo, taking place October 31 – November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world.
The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long development cycles that produce software that is obsolete at launch. DevOps may be disruptive, but it is essential.