{"id":4489,"date":"2017-10-25T09:25:58","date_gmt":"2017-10-25T09:25:58","guid":{"rendered":"http:\/\/www.odbms.org\/blog\/?p=4489"},"modified":"2017-10-25T09:25:58","modified_gmt":"2017-10-25T09:25:58","slug":"on-vertica-and-the-new-combined-micro-focus-company-interview-with-colin-mahony","status":"publish","type":"post","link":"https:\/\/www.odbms.org\/blog\/2017\/10\/on-vertica-and-the-new-combined-micro-focus-company-interview-with-colin-mahony\/","title":{"rendered":"On Vertica and the new combined Micro Focus company. Interview with Colin Mahony"},"content":{"rendered":"

”\u00a0There has been no uncertainty with respect to the Micro Focus leadership\u2019s commitment to building on the great brand and product we have developed at Vertica.”–\u00a0Colin Mahony<\/strong><\/p><\/blockquote>\n

I have interviewed\u00a0Colin Mahony,\u00a0<\/strong>SVP & General Manager, Vertica Product Group, Micro Focus. <\/em>
\nIn this interview we covered the recent spin-off of HPE software into a new combined Micro Focus company, and how this is affecting Vertica. We also covered the new release of \u00a0Vertica 9, and the importance of Big Data analytics.<\/p>\n

RVZ<\/p>\n

Q1.With the recent spin-off of HPE software into a new, combined Micro Focus company, do you see things changing for Vertica?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>From a product development, sales and customer support perspective \u2013 it\u2019s been business as usual at Vertica leading up to and since the spin-merge with Micro Focus. Our focus, as always, is to build the best possible product and deliver world-class support for our growing customer base. That won\u2019t change any time soon.<\/p>\n

The biggest changes I see post spin-merge is that Vertica is now part of a pure-play software company, rather than a business where a majority of revenue comes from hardware. Running a software company is a lot different than running a hardware business.\u00a0Under HPE, the software assets sometimes struggled in establishing their own identify as part of a much larger hardware business.\u00a0 Micro Focus<\/a> on the other hand is designed from the ground up to build, sell and support software for our customers, that\u2019s all we do. The new, combined Micro Focus is the 7th<\/sup> largest pure-play software company in the world, and we have the global scale to be an industry shaper.
\nBut maybe even more exciting is the level of support and GTM independence that we are already seeing from Micro Focus in support of Vertica. You have likely seen Vertica\u2019s logo and you\u2019ll continue to see more of that, especially on the Vertica.com<\/a> website that we launched in February and that already has almost 1 million page views! We have been structured uniquely in the new Micro Focus and this gives me complete confidence in our future. I\u2019m genuinely excited about the opportunity to be in a business that is dedicated and focused purely on software \u2013 especially software with analytics built in, the new Micro Focus company mission – and the business value of that software for customers.<\/p>\n

Q2. There are concerns that Micro Focus may end up managing mature software assets of HPE and extending their shelf life, rather than actively investing in feature developments. What is your take on this?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>I fundamentally disagree with that. Micro Focus helps companies bridge their existing technologies with new infrastructure and applications. It helps them maximize their ROI while embracing innovation to address the opportunities of the new Hybrid IT and analytics-driven environment. It\u2019s frankly wrong to expect customers to make investments in core technologies without working hard to maximize the investment in those technologies. Over the years, Micro Focus has taken core assets and made them modern, delivering significant value to the company and our customers.<\/p>\n

It\u2019s also important to note that the new, combined Micro Focus has an incredible depth and breadth of software assets in its portfolio \u2013 covering DevOps, IT Operations, Cloud, Security, Big Data and more \u2013 not all of which are mature products.
\nTake SUSE<\/a> for instance, a Micro Focus product and the fastest growing open Linux<\/a> platform. I\u2019m very impressed with the approach that Micro Focus has on supporting growth businesses like this. I have the very same expectations for our Vertica business, especially because this is a massive new opportunity for Micro Focus, which prior to the spin-merge did not have a Big Data offering.
\nThis means no confusion, no duplication of resources, and a lot of potential because we know that every company in virtually every industry is thinking about how to leverage analytics at the core of everything they do, and again, why \u201canalytics built in\u201d is at the core of the new company\u2019s mission.<\/p>\n

Q3. Will Micro Focus continue to develop Vertica?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>There has been no uncertainty with respect to the Micro Focus leadership\u2019s commitment to building on the great brand and product we have developed at Vertica. Since the spin-merge with Micro Focus was first announced in 2016, we have actually been reinvigorating the Vertica brand name, all based on the recognition that Micro Focus has a tremendous market opportunity in front of it with the advent of Big Data and the growing importance all companies are placing on the value of analytics. You can see this commitment with the build-out of our new website, www.vertica.com<\/a>, our presence at industry trade shows and conferences, and more.<\/p>\n

In a recent interview<\/a>, Chris Hsu<\/a>, CEO of the new, combined Micro Focus, expressed his commitment to big data analytics \u2013 and specifically Vertica \u2013 as the number one area he is most excited to focus on and grow within the portfolio. It\u2019s an exciting time to be part of Vertica. We have an incredible opportunity in front of us.<\/p>\n

Q4.\u00a0Micro Focus now has a number of software assets covering Hybrid IT, DevOps, Security and more, where analytics is critical. Does or will Vertica play a role in those products?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>Absolutely. Not only is there a strong commitment in continuing to develop Vertica as a product and brand, there\u2019s wide recognition within Micro Focus that predictive analytics<\/a> is critical for the success of data-centric enterprises, and therefore a critical component to the breadth of assets in our own portfolio.<\/p>\n

Vertica is an ideal solution for embedded analytics<\/a>. Businesses that embed Vertica stand out from the competition and deliver higher value to customers.\u00a0Specifically designed for analytic workloads, Vertica\u2019s speed and performance, advanced analytics, ease of deployment, and support for data scientists make it tailor-made for embedding. We now have an opportunity to embed these great analytical features in a range of Micro Focus software assets, something we\u2019ve already begun to do in application delivery management, IT operations and security. As I\u2019ve said, a core part of our company\u2019s core mission moving forward is to provide customers with enterprise-grade scalable software with analytics built in<\/em>. I see this as a large and growing opportunity for innovation here at Micro Focus.<\/p>\n

Q5.\u00a0You recently released Vertica Version 9, with major enhancements in cloud deployments and separation of compute and storage. Are these common themes for Vertica moving forward?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>They are. Vertica has always been 100% committed to helping our customers deploy advanced analytics free from underlying infrastructure and hardware lock-in. We\u2019ve seen that legacy data warehouse solutions have forced many enterprises into rigid and high-cost proprietary hardware and analytics solutions supporting only limited data formats and deployment options. As data formats and storage locations continuously evolve, organizations require a powerful and unified solution to analyze data in the right place at the right time, with the performance and economics that the business requires. Our continued commitment to this principle \u2013 and our support for any major cloud platform, whether AWS<\/a>, Azure<\/a> or GCP<\/a> \u2013 is foundational to Vertica\u2019s core.<\/p>\n

Separation of compute and storage is a logical extension of this product development ethos. Vertica\u2019s beta release of its new Eon Mode architecture<\/a>, offering separation of compute and storage, provides rapid elastic scaling up and down of the Vertica cluster, with just-in-time workload-based provisioning.
\nAn intelligent, new caching mechanism on the nodes enable organizations to benefit from Vertica’s industry-leading query performance. Companies in the AWS ecosystem will be able to leverage AWS S3<\/a> for storage and Vertica\u2019s query-optimized analytics engine for processing speed to capitalize on cloud economics.<\/p>\n

You can expect continued product development and investment in these areas.<\/p>\n

Q6. With the explosion of data lakes and other external data storage (including Hadoop, AWS S3, etc.), does this complicate the analytical database market or change the dynamics of how and where you analyze data?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>It certainly changes the big data landscape. Hadoop <\/a>has been a boon to companies and organizations that want to store vast new volumes of unstructured data cheaply in the form of a data lake. AWS S3 has extended that cheap storage to the cloud. Although Hadoop stores massive volumes of unstructured data, performing analytics on Hadoop proved challenging. Despite this challenge, companies did not want to move large amounts of data in and out of their Hadoop data lakes. As a result, more and more companies were looking to build out enterprise-grade SQL analytics on top of their Hadoop investments. This created a tremendous opportunity for Vertica, and Vertica for SQL on Hadoop<\/a> was born. Vertica SQL on Hadoop is the same binary, the same core engine, with the ability to deploy natively on Hadoop nodes. Since then, we\u2019ve continued to innovate on how Vertica integrates with the various Hadoop distributions and file formats. We\u2019ve leveraged our years of experience in the Big Data analytics marketplace to enable organizations to analyze their data not only in place, but in the right place \u2013 without data movement \u2013 while supporting any major cloud deployment for fast and reliable read and write for multiple data formats.<\/p>\n

Starting with the release of Vertica 8, users could derive more value from their Hadoop data lakes with Vertica’s high-performance Parquet<\/a> and ORC<\/a> Readers that enable users to securely access and analyze data that resides in Hadoop data lakes without copying or moving the data. And now with our latest Vertica 9 release<\/a>, we\u2019ve introduced a new HDFS Parquet writer \u2013 built on Vertica\u2019s fast and reliable ability to not only read, but now write data and results on HDFS \u2013 to derive and contribute immediate insights on growing data lakes. Organizations can use Vertica 9\u2019s flexible and expanded deployment options across on-premise, private, and public clouds, and on Hadoop and AWS S3 data lakes, to adopt a best-fit analytical solution.<\/p>\n

The days of having to move data in and out of various databases and data lakes is coming to an end. In the future, more and more companies will bring analytics to the data, analyzing it in place. We believe Vertica is working at the forefront of this market transformation.<\/p>\n

Q7. Over the last few releases, Vertica has made significant advancements in the area of in-database machine learning. How do you see this set of capabilities contributing to Vertica\u2019s strategy and the success of your customers?<\/strong><\/p>\n

Colin Mahony:\u00a0<\/strong>There\u2019s no doubt that machine learning<\/a> and predictive analytics are, and will continue to be a core differentiator for organizations. In today\u2019s data-driven world, creating a competitive advantage depends on your ability to transform massive volumes of data into meaningful insights. Vertica has always supported the world\u2019s leading data-driven organizations with the fastest SQL and extended SQL analytics. And now, by building machine learning functions directly into Vertica\u2019s core \u2014 with no need to download and install separate packages \u2014 we are transforming the way data scientists and analysts across industries interact with data; removing barriers and accelerating time to value on predictive analytics projects. And it\u2019s not just about developing the right algorithms and models. Our goal at Vertica is to support the entire machine learning and predictive analytics process, from data preparation to model evaluation and deployment \u2013 all using Vertica\u2019s industry-leading scalability and performance. I\u2019m incredibly excited to see these features transform data science and predictive analytics projects within our customer base, and for this reason, in-database machine learning<\/a> will play a major role in Vertica\u2019s future, and the future of our customers.<\/p>\n

Our commitment to this area can be seen in the latest Vertica 9 release, which provides a comprehensive set of new Machine Learning algorithms for categorization, overfitting and prediction to enhance processing speed by eliminating the need for down-sampling and data movement. There\u2019s also support for new data-preparation functions for deriving greater meaning from the data, while improving the quality of analysis, and a streamlined end-to-end workflow that simplifies production deployment of Machine models \u2013 particularly for customers that embed Vertica and require the ability to replicate models across clusters.<\/p>\n

————————<\/p>\n

\"c\"<\/a>
\nColin Mahony<\/strong>, SVP & General Manager, Vertica Product Group, Micro Focus<\/em><\/p>\n

Colin Mahony leads the Vertica Product Group for Micro Focus, helping the world\u2019s most data driven organizations to leverage and monetize their business data. Vertica was founded in 2005 and is one of the industry\u2019s fastest growing, advanced analytics platform with in database machine learning, the ability to analyze data in the right place, and freedom from underlying infrastructure. Micro Focus also leverages Vertica to deliver embedded analytics across a very broad portfolio of enterprise grade software. <\/em><\/p>\n

In 2011, Colin joined Hewlett Packard as part of the highly successful acquisition of Vertica, and took on the responsibility of VP and General Manager for HP Vertica, where he guided the business to remarkable annual growth and recognized industry leadership. Colin brings a unique combination of technical knowledge, market intelligence, customer relationships, and strategic partnerships to one of the fastest growing and most exciting segments of HP Software.<\/em><\/p>\n

Prior to Vertica, Colin was a Vice President at Bessemer Venture Partners focused on investments primarily in enterprise software, telecommunications, and digital media. He established a great network and reputation for assisting in the creation and ongoing operations of companies through his knowledge of technology, markets and general management in both small startups and larger companies. Prior to Bessemer, Colin worked at Lazard Technology Partners in a similar investor capacity.<\/em><\/p>\n

Prior to his venture capital experience, Colin was a Senior Analyst at the Yankee Group serving as an industry analyst and consultant covering databases, BI, middleware, application servers and ERP systems. Colin helped build the ERP and Internet Computing Strategies practice at Yankee in the late nineties.<\/em><\/p>\n

Colin earned an M.B.A. from Harvard Business School and a bachelor\u2019s degrees in Economics with a minor in Computer Science from Georgetown University. He is an active volunteer with Big Brothers Big Sisters of Massachusetts Bay and the Joey Fund for Cystic Fibrosis as well as a mentor and board member of Year Up Boston.<\/em><\/p>\n

————–<\/p>\n

Resources<\/strong><\/p>\n

–\u00a0What\u2019s New in Vertica 9.0?<\/a>, ODBMS.org, 22 Oct, 2017<\/p>\n

–\u00a0What\u2019s New in Vertica 9.0: Eon Mode Beta<\/a>,\u00a0ODBMS.org,\u00a022 Oct, 2017<\/p>\n

–\u00a0Vertica Version 9.0<\/a>,\u00a0ODBMS.org, 22 Oct, 2017<\/p>\n

–\u00a0Micro Focus Introduces Vertica 9<\/a>, ODBMS.org, Sept. 27, 2017<\/p>\n

Related Posts<\/strong><\/p>\n

–\u00a0On Data Analysis. Interview with Rob Winters<\/a>, ODBMS Industry Watch,\u00a0January 9, 2017<\/p>\n

Follow us on Twitter: @odbmsorg<\/a><\/strong><\/p>\n

##<\/p>\n","protected":false},"excerpt":{"rendered":"

”\u00a0There has been no uncertainty with respect to the Micro Focus leadership\u2019s commitment to building on the great brand and product we have developed at Vertica.”–\u00a0Colin Mahony I have interviewed\u00a0Colin Mahony,\u00a0SVP & General Manager, Vertica Product Group, Micro Focus. In this interview we covered the recent spin-off of HPE software into a new combined Micro […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[35,1155,1161,66,1164,97,903,1159,1163,1162,239,1154,350,1153,1158,1157,700,549,603,1160,1156],"_links":{"self":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4489"}],"collection":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/comments?post=4489"}],"version-history":[{"count":9,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4489\/revisions"}],"predecessor-version":[{"id":4500,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/4489\/revisions\/4500"}],"wp:attachment":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/media?parent=4489"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/categories?post=4489"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/tags?post=4489"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}