Cloud BI and Analytics Options Aren’t Just for Cloud Data

Doug Henschen

Former Vice President and Principal Analyst
Constellation Research

Doug Henschen is former Vice President and Principal Analyst where he focused on data-driven decision making. Henschen’s Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Henschen's research acknowledges the fact that innovative applications of data analysis requires a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data-visualization, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies. Insight-driven business models are of interest to the entire C-suite, but most particularly chief executive officers, chief digital officers,…...

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Exploit cloud advantages and data from on-premises, external sources as well as cloud stores to drive deeper insight, innovation and new business models.

The center of data gravity is shifting outside the walls of the enterprise. In fact, Constellation estimates that by 2020, at least 60 percent of the data that organizations consider to be mission-critical will live outside the four walls of the enterprise.

The move to cloud computing is the leading contributor to this trend, and it will change how organizations handle business intelligence (BI) and analytics. But don’t make the mistake of thinking that cloud-based BI and analytics options are just for data that’s created in the cloud. Rather, these systems are ideal for the increasingly common scenario in which organizations are gaining insight from data from all over the place.

Yes, it will be a hybrid world, but that’s not a binary choice between data that’s in your corporate data center and data born or uploaded into your cloud stores. Some of the data you need will be in software-as-a-service applications, some in partner networks, some in social networks, some in mobile apps running on cloud infrastructure, and some in third-party sources, such as weather feeds, demographic enrichment sources, and government data sets.

As I explain in my latest report, Three Imperatives for Innovating with Cloud BI and Analytics,  the opportunity is to take advantage of cloud flexibility, ubiquity and architecture to tap into many sources, support important new analyses and surpass the old barriers of BI. That advantage isn’t just reduced initial cost and administrative overhead (you can achieve that through hosting of conventional software, but that’s not what Constellation would call true, multi-tenant cloud BI and analytics).

The report addresses three priorities that companies should pursue as they move toward next-generation deployments:

1. Make the most of cloud advantages including flexibility and elasticity, so you can quickly tap new data sources as they emerge, wherever they emerge. Further, with cloud services it’s easier to embed insights into applications and expose them externally to partners and customers.
2. Take advantage of external data. As the balance of mission-critical data shifts, cloud-based BI options are well suited to blend and analyze data from myriad external sources, including SaaS apps, social networks, mobile apps, sensor networks, and third-party data providers as well as on-premises sources.
3. Advance innovation and create new business models. Think beyond dashboards and reports. Innovators are using analytics to drive insight-based differentiation, data brokering and data-monetization. Connected-car and predictive maintenance applications, usage-based pricing, performance benchmarks, insight services and predictive recommendations are just a few examples of the kinds of innovations that are creating value and opening up new sources of revenue.

The 21-page report includes two figures, a table depicting Constellation’s view of the evolution from mass personalization systems to cognitive intelligence systems, and a listing of five styles of cloud-based BI and analytic products and representative vendors. To learn more about the report and its findings and recommendations, download this free excerpt, which includes the table of contents, executive summary and introductory section.

Related Reading:

Inside Oracle Adaptive Intelligent Apps
Tableau Sets Stage For Bigger Analytics Deployments
Qlik Gets Leaner, Meaner, Cloudier

The use of Digital Twins to bring Physical and Digital Services together

Andy Mulholland

Vice President and Principal Analyst, Constellation Research
Constellation Research

Andy Mulholland is Vice President and Principal Analyst focusing on cloud business models. Formerly the Global Chief Technology Officer for the Capgemini Group from 2001 to 2011, Mulholland successfully led the organization through a period of mass disruption. Mulholland brings this experience to Constellation’s clients seeking to understand how Digital Business models will be built and deployed in conjunction with existing IT systems. Coverage Areas Consumerization of IT & The New C-Suite: BYOD, Internet of Things, IoT, technology and business use Previous experience: Mulholland co authored four major books that chronicled the change and its impact on Enterprises starting in 2006 with the well-recognised book ‘Mashup Corporations’ with Chris Thomas of Intel. This was followed in…...

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The Industrial Internet Consortium and Industrie 4.0 are seeking to transform not just manufacturing processes through applying IoT sensing for incremental improvement, but the entire process of Product Lifecycle Management, PLM. Their approach combines a number of technologies, and existing applications of technology, into the ubiquitous integrated and connected ecosystems of IoT. The concept of ‘Digital Twins’, the creation of both a physical entity with a corresponding digital entity, is core to this transformation.

In September 2015 The Economist headlined an article; ‘The digital Twin; could this be the 21st-century approach to productivity enhancements?’ The article went on to state; ‘The real advantage of the digital twin, however, materializes when all aspects, from design to real-time data feed, are brought together to optimize over the lifetime of the asset’.

In a similar article the World Economic Forum has drawn attention to the importance of Digital Twins under the headline, ‘Can the digital twin transform manufacturing?’. Yet outside of those directly concerned the concept is little recognized, or understood, even in many manufacturing companies. Certainly not in companies providing Machine Servicing and Support who will perhaps feel even greater impacts on their business model.

Creating a fully functional Digital Twin is a logical enhancement to the increasing sophistication in 3D design to develop the starting point for a complete Digital Services Product Lifecycle Management capability.  Complex products are increasing using enhanced 3D designs to model the product for optimization in various aspects; simplicity for manufacturing, operational efficiency, maintainability, predicted wear and failure etc. IoT allows the performance of real installed physical machines to be compared with the predicted behavior observed in the Digital Twin pre production model, and in the resulting physical prototypes.

The simultaneous collection of data, using IoT sensing and connectivity, from operating physical machines can be used to run reiterations of the digital machine model to further increase the accuracy of predicted behavior. The manufacturers of complex products such as GE and Siemens, both leaders in applying Digital Twins to their products, have already adopted much of the necessary technology to improve their in-house design and manufacturing quality.

Riemer, the VP of Aerospace and Defense Strategy at Siemens describes the new business value as moving beyond ‘Digitisation’ of products to ‘Digitalisation’ of process by the use of IoT to form ‘golden threads’ of connected information.  “It’s about relating information,” he said. “It’s about understanding the ‘why’ and the longer the reach of the digital thread from your company’s enterprise, the more likely it is to become a major influence on how you complete certain processes’.

The question is what are the certain processes? In the emerging market built around Digital Services, ranging from ‘Power by the Hour’ through to Maintenance Service contracts with tightly specified performance criteria, Digital Twins represents a new business proposition closely aligned to the Digital Services economy.

‘Manufacturing’ a Digital Twin at the same time as manufacturing the physical version provides the manufacturer with a Digital product as a basis for creating various new ‘Services’ products. In the Digital Services market place this is an important step as many manufacturers look for new revenue streams. Immediate possibilities building on current trends around OpEx cost provisioning allow the manufacturer to achieve ongoing cost optimization. The ability to load the model with actual data experienced by different customers allows individual customization of operating machinery provided on ‘pay per use’, or ‘power by hour basis’.

Manufacturers operating traditional Service Maintenance contracts gain the ability to increase the accuracy of predicted failure times and costs, as well as adjusting any settings to reduce wear. The result from a large number of deployed machines will enable cross use of the data for faster access to pinpointing insights to increase profitable operation. This is the point where Machine Learning brings true Business value by large-scale examination of results pinpointing best practice.

The impacts are likely to be rather different for existing Service Maintenance Businesses, particular if independent, and therefore lacking access to the Manufacturers Digital Twins data. Training, certification, and representation of a particular Enterprises products would need to extend to include access to some aspects of a Digital Twin on the manufacturers Cloud Service. At the very least a new degree of interactive data exchange would seem to be called for to ensure that Machinery under indirect maintenance provide data to manufacturers, the so called Golden Thread of connected data referred to earlier.

The manufacturer has the opportunity to supply new technology-based services to their aligned Enterprise Service Representatives including, as an example, Virtual Reality to guide Service Engineers working on their products. These are potentially both new revenue streams, but bring the customer benefit of faster, cheaper, better maintenance.

The question that this, and other associated changes arising from IoT, bring is that on one hand the market shift to interconnected and interactive Ecosystems of Business Partners increases the numbers of Player visibly competing for work. On the other hand it introduces the need for greater Business collaboration and alignment in sharing data.

Software Solution vendors such as Salesforce.com and SAP recognize the implications and are working on enhancing their current offerings, both can claim to improve Predictive and Actual Maintenance, even though their approaches are very different. Salesforce focus on making the performance of the person and their ability to act with the data much more effective; whilst SAP focuses on the creating more effective processes to driven the engagement. Both offer Service Maintenance companies’ highly effective ways to use IoT with its new forms of data transforming the effectiveness of Maintenance. Longer term the use of Digital Twins leads towards innovations such as instant spare parts availability through 3D printing generation.

The nature of the Ecosystem model with collaboration between manufacturers and Maintenance companies is reflected in new partnerships in the Technology Industry. Salesforce is partnered with GE in building a new level of interactive relationships with its customers that goes hand in glove with the interactive Business model of Digital Services. SAP is in a strategic alliance with Siemens to build and host advanced capabilities around IoT and maintenance.

The future path towards creating Digital Twins of many physical objects, possibly even including people eventually, looks to deliver significant enough business value to ensure that large complex machinery and devices will drive a rapid take-up. However that does not mean the every machine, or device is complex enough to warrant a full Digital Twin, and of course there is a very substantial installed base of existing machinery that requires some level of Physical and Digital alignment. Past blogs have dealt with the need to assemble contextual data with the event data from IoT devices, notably; ‘Why IoT devices need be digital assets’.

For independent Service Maintenance companies familiarization with the more readily accessible capabilities of Digital Assets are the starting point for building their own databases and perhaps customer models as a key strategic initiative. In the Digital Services ecosystem the ownership of data is a key differentiator, and that data could be on the Machine itself, or it could be on its deployed use at a customer site.

Both are needed and are likely to be important trade items in the future ecosystems of Machine based Services based business. Manufactures expertise may lay in the product Digital Twin, whilst Maintenance companies may own equal expertise in the deployment and use.

Appendix;

Digital Twins - GE

http://siliconangle.com/blog/2016/11/15/how-to-watch-exclusives-from-ge-minds-machines-gemm16/

http://www.sfchronicle.com/business/article/GE-chief-Jeff-Immelt-to-Silicon-Valley-Our-time-10616802.php

http://www.businesswire.com/news/home/20161115005632/en/GE-Expands-Predix-Platform-Advance-Industrial-Internet

Digital Twins – Siemens;

http://www.siemens.com/innovation/en/home/pictures-of-the-future/industry-and-automation/digital-factory-plm.html

http://www.siemens.com/customer-magazine/en/home/industry/digitalization-in-machine-building/the-digital-twin.html

http://www.plm.automation.siemens.com/en_gb/products/simcenter/intro/?stc=gbiia429995&s_kwcid=AL!463!3!112711271364!p!!g!!digital%20twin&ef_id=WCtHxwAAAaNs2gvD:20161115173711:s

Salesforce - Field Service Engineer

https://www.salesforce.com/products/service-cloud/features/field-service-lightning/

SAP – Predictive Maintenance and Service

https://help.sap.com/pdm-od

AWS reInvent 2016 - Growth at full speed

Holger Mueller

Vice President and Principal Analyst
Constellation Research

Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.  Coverage Areas: Future of Work Tech Optimization & Innovation  Background: Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...

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We had the opportunity to attend AWS reinvent, held this week in Las Vegas, from November 27th till December 2nd 2016. It was the largest reinvent ever, with over 32000 attendees… not only to me it appeared that reinvent becomes the new VMWorld – the yearly get together of the IT industry. Only ones missing were the hardware vendors, for obvious reasons. 

 

 

So take a look at my musings on the event here: (if the video doesn’t show up, check here)

 

No time to watch – here is the 1-2 slide condensation (if the slide doesn’t show up, check here):
 

 

 

Event Report - AWS reInvent 2016 - Growth at full speed from Holger Mueller

Want to read on? 

 

Here you go: Always tough to pick the takeaways – but here are my Top 3:

The battle for load wages on – All IaaS players need to attract load to their cloud in order to achieve and maintain scale. This was also obvious at reinvent as AWS made several moves to get more load to AWS. The prime targets in this race are the SaaS players, as a partnership with a SaaS player gives access to a lot of conform, standard and repeatable load. Even better the SaaS player will advertise and help move its customers over. So that AWS wanted to have Workday is no surprise. That Workday picked AWS for production loads was a little more, given the recent decision to run development and test loads on IBM Cloud (read here). Earlier this year AWS got commitments from Salesforce (see here) and SAP for BW4HANA (see here). The next lower priority to get load is to have enterprises build their next generation applications on the vendor’s platform and AWS provided a number (see below) of new services to make it attractive to build these. The prime ones are around BigData and Machine Learning – and AWS announced Amazon Athena (query S3 with SQL) and AWS Glue (ETL and more), Amazon AI, Rekognition, Polly and Lex). And once they are built you need to make it easy to operate on the platform, it needs to be secure (AWS Shield), and efficient (Amazon Lightsail, EC2 Systems Manager, AWS CodeBuild, X-Ray and Batch). And customers want to get more value out of their code (AWS Snowball Edge – runs AWS Lambda) and use more of their skills (adding C# to AWS Lambda, adding PostGreSQL to Aurora). But a limitation can be the data movement, so the catchy announcement was the AWS Snowmobile, a container that can move up to 200 PB from on premises to cloud. All are valid offers and arguments for enterprises to use AWS as their IaaS. 
 

All reInvent 2016 announcements

Ease of use and consumption – With the growth of AWS – now at over 3.5k+ capabilities – if you add all the innovations up from the start) has become a complex system. Education was prominent as was certification. We are always fans of valid and hard certification tests, as they help enterprises to know which consultant / programmer can do what. But at the core it is about software based improvements and what stood out to me were AWS X-Ray, AWS CodeBuild and the enablement of CI and CD processes in AWS.

 

All of AWS in 1 slide

AWS doubles down on AWS Lambda – Since its announcement, AWS Lambda has been an interesting and differentiating way for building code in AWS, bring the code to the data, only pay when used etc. AWS Lambda as a language and platform become now more prominent as AWS uses Lambda as well to move code from AWS outside the connected cloud environment, e.g. on the new AWS Snowball Edge. Somebody deserves more than paycheck and bonus of adding the light weight application server to S3, which in my guess is the platform for all of this. This is good news for enterprises, as AWS proprietary code build on AWS Lambda can go more places. 

 

Vogels walks by AWS Athena

My picks – Very hard to pick the Top announcements for each day, maybe AWS (and me) need to think of different categories (e.g. developer, CIO, data scientist, DevOps etc.) – but here you go: For Day #1 for me it is Athena – being able to query data in S3 with well-known SQL is a win win. More data gets accessible with the #1 query language. And given that S3 is one of the major attractions of AWS, a key move by the vendor. For Day #2 it is AWS Glue: Every year AWS tries to take a piece of traditional IT spend and offer an alternative – it was Amazon Workspaces 3 years ago, Amazon Aurora 2 years ago and Amazon QuickSight last year – now it is AWS Glue – an ETL and more to get data moved, enriched, etc. to give users more time to do what matters: Analytics. 
 

Vogels announces AWS Glue

 

MyPOV

AWS growth keeps going strong, frankly at an amazing rate. By now it has attracted every services player (it has signed up over 10k partners in 12 months), has been evaluated by all major ISVs, is the default platform for most startups, and few enterprises are not running one piece of automation or the other on the platform. And growth both in functionality as well as business does not seem to slow down, not even showing a sign of weakness. Au contraire, the number of new capabilities YoY has increased by almost 50% - from a base of 700 to 1000. This is all good progress and sailing by AWS, making it the clear market leader for IaaS and the PaaS related services on top of it. And new use cases, like e.g. IoT was presented in the keynote with Italian energy giant ENEL, continuing the tradition that keynote speakers for IoT come from European enterprises. And AWS is growing up, with a separate partner program, region, country specific events at reinvent, even the stream was subtitle in 4 languages.

On the concern side, AWS was not able to deliver a major ‘All in’ customer to the two keynotes, admittedly GE is a tough act to follow, but I would have expected to see more public traction. Instead we had repeat keynote presenters, e.g. FINRA. Nothing wrong with this, good to see an update. The event was well visited from an international perspective, but apart from ENEL, I didn’t recall non-North American customers presenting. Maybe AWS keeps them stocked for the many regional AWS Summits that happen throughout the year. But these are minor concerns compared to who AWS wants to keep operating: Operating models are different when you are the web serviced division of an online retailer with a few 100Ms in revenue (as AWS was 5-6 years ago), experimenting with services and seeing what ‘sticks’ (CTO Vogels back then) – vs. being a 10B+ key IT infrastructure provider. I asked CEO Jassy about this and his answer was clear – AWS will not slow down. And while 1000 new capabilities will be manageable it will be 1500 (extrapolation from me here) next year, and close to 3500 in 2 years, if AWS keeps pace. At some point AWS will have to package, simplify, provide version to its offering – maybe the start will be separate conferences as the Sands Convention Center was at times over the limits of its capacity.

But for now, all is well for AWS, it needs to catch up in some areas like e.g. Machine Learning and it was interesting to see how AWS execs positioned this, but that was bound to happen. And frankly is not expected by enterprises either, leading in all aspects of next generation applications is no longer realistic given the wide range of products and services offered. And AWS has achieved what it wanted to get done since a long time, be the platform that cannot be ignored and must be evaluated when enterprises make cloud infrastructure decision. Stay tuned for more.


Want to learn more? Checkout the Storify collection below (if it doesn’t show up – check here).




 

Find more coverage on the Constellation Research website here and checkout my magazine on Flipboard and my YouTube channel here.

2012, 2013, 2014, 2015 & 2016 (C) Holger Mueller - All Rights Reserved