Wikibon 2018 Predictions

1. Wikibon’s 2018 Predictions Peter Burris David Floyer James Kobielus George Gilbert Neil Raden DavidVellante Stuart Miniman

2. Who IsWikibon? Most Authoritative Communities Best Ideas Packaged for Actionable Engagement • 4,000 thought leader video interviews per year • 40,000 video clips • Crowd-based research techniques • Digital business advisory services ©Wikibon 2017 2

3. What Is Digital Business? Peter Drucker “The purpose of business is to create and keep a customer.” Wikibon. “Digital businesses apply data to create and keep a customer.” ©Wikibon 2017 3

4. Essential Digital Business Capabilities Capture Data • internet of things and people CreateValue from Data • Big Data and AI Enact Based on Data • Systems of Agency Turn More Data Into Work Cloud Optimization ©Wikibon 2017 4

6. GDPR Reshuffles Data Governance – and Brands • GDPR mandates data governance rules and practices • New role:The Data Protection Officer (DPO) • Example: pittance fines for data breaches in the US; $160B in fines under GDPS • New bills being introduced in US Congress, but GDPR will be strictest privacy regime for a while. Wikibon Prediction.The European Union’s General Data Protection Regulation (GDPR) goes into full effect 28 May 2018 and will catalyze changes far beyond the EU’s borders. As many as 15% of global enterprises will adopt GDPR practices globally, especially those firms that operate mainly in B2B markets. By 2023, privacy and trust will be explicit features of B2B brands. GDPR

7. The Rise of the CDigiO • Major theCUBE topic in 2017 • Titles and roles remain fluid; GDPR and shareholder scrutiny will force more structure • CDigiO works with (for?) COO to define and operationalize • Strategic digital capabilities • Crucial data flows • Data monitization schemes COO CDigiO CISO CIO CDO/DPO CTO CPO Wikibon Prediction.The Chief Digital Officer (CDigiO) gains operational traction in business. Starting out largely as a strategy role, the executive suite begins to entrust more operational responsibility to the CDigiO. In 2018, 10% of enterprises will position the CDigiO above the CIO (technology), CISO (security), CDO (data and records), and CPO (protection and privacy). By 2022, that figure will grow to 40%-50%.

9. Network Costs Impact Edge Data Choices • IoT and “edge analytics” increasingly are synonyms. • Today’s data exhaust may be tomorrow’s data platinum. • Latency is fixed, bandwidth costs are not. • Lots of politics in front of us (lobbying, OT/IT), but bandwidth pricing will shape IoT data reduction requirements. Wikibon Prediction. IoT buzz will reach the realization that network costs are 3-5X greater than hardware costs. In fact, IoT hardware costs will be a secondary consideration in building out an instrumented network. Large hardware providers will not be prime differentiators. In 2018, we see Amazon and Google positioning as leaders in providing communication alternatives to the existing common carriers, with a build-out of the networks by 2020.

10. Autonomous Edge Drives Bespoke AI • “If software is eating the world, the biggest bites are taken at the edge.” • When latency dictates autonomy, ”learning by doing” is the primary option for intelligent devices. • Will have far-reaching impacts on AppDev, profoundly impacting practices related to access to data sources, testing, validation, etc. Wikibon Prediction. Autonomous edge devices, powered by AI-infused componentry that are trained through reinforcement learning, are becoming ubiquitous. By year-end 2018, more than 25 percent of enterprise AI application-development projects will involve autonomous edge devices and that, by that time, more than 50 percent of enterprise AI developers will have gained familiarity with reinforcement learning tools and techniques.

12. Data Scientists Do More Data Science • As data science disciplines mature, the masters are separating from the minions. • Data science tools are codifying “master” practices. • Won’t diminish the value of real data science, but • May diminish some of the esteem. • Will increase specialization – especially best practices in horizontal and vertical domains. • The best and brightest data scientists still gravitate to digital giants and start-ups. Wikibon Prediction.The general availability of ML and AI tools will tend to demystify the practice and also deprecate the lofty position that data scientists occupied for a short time. However, organizations engaged in true data science and research & development of fundamental AI algorithms will drive the progression of the discipline. The 80% data scientist (80% wrangling data, 20% doing data science) will see a near reversal in 2018.

13. Big Data Open Source Consolidation Wikibon Prediction.Vendors of big data open source software are going to start consolidating through mergers and roll-ups in 2018. Kafka Streams Spark, Flink NoSQL NewSQL Microservice Ingest Process Analyze ServePredict Compute Storage Kafka Splice Machine, Snappy Data, MemSQL, Snowflake Kudu, Cassandra, Redis, Iguazio

15. Exploiting AI in Applications Wikibon Prediction. In 2018 leading-edge enterprises will realize that the scarcity of data science talent means they can’t build models and applications from scratch. Rather, they will have shift from building models to leveraging public cloud vendors’ pre-trained models via developer-ready APIs.

16. Automation Impacts Development,Too • AppDev tedium remains the quality enemy and morale killer. • AI-related technologies can be applied to AppDev productivity challenges. • Not a silver bullet, but: • Developers will factor AI-support in tool selection. • AI-enhanced development tools will catalyze adoption of AI tooling and services for business app domains. Wikibon Prediction. Auto-programming will become a centerpiece of enterprise application development. By year- end 2018, the latest auto-programming techniques – including machine learning (ML) and robotic process automation (RPA) – will be incorporated into the top tier integrated development environments (e.g., MSFT Azure, IBM Bluemix).

17. Serverless, Developer More • Who needs (to know about) infrastructure? • Benefits • Scale and speed • Agile-friendly • DevOps-friendly • Cheaper to move function than data, especially at the edge. Wikibon Prediction. Functional methods will become the mainstream approach for building lightweight cloud microservices. By year-end 2018, more than 50 percent of new microservices deployed in public cloud will be deployed in serverless environments. However, due to the embryonic adoption of serverless, on-premises platforms, fewer than 10 percent of new functional code-builds in private clouds will use functional code.

19. True Private Cloud Makes Data Happy Wikibon Prediction. Increasingly, the mantra for cloud architects will be, “The cloud experience, where the data demands,” and data “demands” will be defined largely by latency, costs, data governance, and IP protection.True Private Cloud (TPC) technologies will gain increasing favor, growing larger than the public IaaS market by 2024.

20. Multi-Cloud? Naturally Wikibon Prediction. Digital businesses are pursuing a wide array of outcomes that will be impossible to handle within single- source public clouds. Multi-cloud will be a feature of almost all enterprise digital business strategies. Kubernetes is emerging as the key technology for managing multi-cloud workflows. By 2020, 60% of developer teams building and sustaining multi- cloud, enterprise applications will use Kubernetes, making Kubernetes the leading foundation for multi-cloud ecosystems. Public CSP SaaS SaaS Public CSP True Private Cloud True Private Cloud Edge Edge Data Center Data Center Data Center

21. NVMe-oF Impact On System Architectures Wikibon Prediction. NVMe-oF is a key component of a new architecture and disaggregation of storage and networking. In 2018, NVMe-oF will be written into most RFPs for scalable hardware. Longer term, the journey to replace SCSI completely has started, with main migration between 2019-2022, and five more years to completely turn the storage product installed base.

22. Rapid Adoption of AI for ITOM Wikibon Prediction. 2018 will be the year that IT Operations and Application Performance Management becomes the first high-volume, horizontal application of machine learning. End-to-EndVisability, More False Positives On Root Causes

23. Action Items • “Digital business = data assets” notion diffusing rapidly. • Start preparing for even more business scrutiny over technology management. • Data indicates technology directions across the board. • Clients: Contact us! support@siliconangle.freshdesk.com

Wikibon 2018 Predictions

Wikibon 2018 Predictions

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Wikibon 2018 Predictions