Cloud Analytics Consortium presents: Analytics in the Cloud: Ready for Primetime

IT is a key player in the digital and cognitive transformation of business processes delivering solutions for improved business value with analytics. This session will step by step explain the journey to secure production while adopting new analytics technologies leveraging mainframe core business assets

Public cloud deployments have become irresistible in terms of flexibility, low barriers to entry, security, and developer friendliness. But the sheer inertia of traditional data lakes make them difficult to transition to cloud. In this talk we'll look at examples of how leading companies have made the transition using open source technologies and hybrid strategies.

Instead of following a "lift and shift" strategy for moving data lake workloads to the cloud, there are new considerations unique to cloud that should be considered alongside traditional approaches related to compute (eg, GPU, FPGA), storage (object store vs. file store), integrations, and security.

Viewers will take away techniques they can immediately apply to their own projects.

The concept of Data lakes evolved to address challenges and opportunities in managing big data.

Organizations are investing massive amounts of time and money to upgrade existing data infrastructures and build data lakes whether on-premises or in the cloud.

This talk will discuss architectures and design options to implement data lakes with open source tools. Also covered are challenges of upgrade & migration from existing data warehouses, metadata management, supporting self-service and managing production deployments.

As an Enterprise customer, you are potentially using IBM Z in a hybrid cloud implementation. Let's understand how to benefit from cloud access to mainframe data without moving it outside z; thereby improving security, reducing integration challenges and answering your GDPR auditor's needs.

Join this webinar where senior researches will present:

1) Big Data Integrator Platform
- Use of Docker and Docker swarm to realize a modular Big Data Platform

2) Semantic Analytics Stack
- Use of Big data distributed processing engines to leverage Scalable
processing for the Semantic Web (RDF data representation, Querying,
Inference, and Machine Learning)

3) Seven societal challenges in Big Data Europe
-Combination of different Big Data tools to create Big Data Value Chain
(Pipeline) for different Use cases representing the societal challenges

Iver van de Zand will talk and demo on the latest SAP innovations for analytics in the cloud. Keywords are live connectivity and the closed loop of combined business intelligence, planning and predictive analytics all in one environment. Fully ready and prepared for big data.

Still confused about this whole Blockchain thing? Interested in investing in digital currencies, but not sure where to start? Want to get a better idea of the threats and opportunities?

David Siegel is a Blockchain, decentralization and business agility expert who has been a high-level management & strategy consultant to companies like Sony, Hewlett Packard, Amazon, NASA, Intel, and many start-ups. David has been praised for being able to explain Blockchain in the most simple and interesting way.

What you will learn:
-What is Bitcoin?
-What is the blockchain?
-What is Ethereum? What is Ether?
-What is a distributed application?
-What is a smart contract?
-What is a triple ledger?
-What about identity and security?
-What business models are at risk?
-What are the opportunities?
-What should we do?

The use of cloud object storage is ramping up sharply, especially in the public cloud, to reduce capital budgets and operating expenses. However, enterprises are challenged with legacy applications that do not support standard protocols to move data to and from the cloud.

Enterprises have developed strategies specific to the public cloud for Data Protection, Archive, Application development, DevOps, Big Data Analytics and Cognitive Artificial Intelligence. However, these same organizations have legacy applications and infrastructure that are not cloud friendly.

Object storage is a secure, simple, scalable, and cost-effective means of managing the explosive growth of unstructured data enterprises generate every day. Gateways enable SMB and NFS data transfers to be converted to Amazon’s S3 protocol while optimizing data with deduplication and providing QoS efficiency on the data path to the cloud.

This webcast will highlight the market trends toward the adoption of object storage and the use of gateways to execute a cloud strategy, the benefits of object storage when gateways are deployed, and the use cases that are best suited to leverage this solution.

Join this webcast to learn:
•The benefits of object storage when gateways are deployed
•Primary use cases for using object storage and gateways in private, public or hybrid cloud
•How gateways can help achieve the goals of your cloud strategy without
retooling your on-premise infrastructure and applications

On December 2nd 2014, provoked by the impact of `Deep Learning’ and other recent scientific and technical advances in Artificial Intelligence, Professor Stephen Hawking released a terrifying warning about the coming technological singularity and the existential danger of AI: "The development of full artificial intelligence could spell the end of the human race. It would take off on its own, and re-design itself at an ever-increasing rate," Professor Hawking said. "Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded".

Fashions in AI come and go - and the hype around so called ‘Deep Learning’ networks is not without precedence - so what is it about ‘nouveau AI’ that warrants such alarm?

Conversely, in this talk, I will endeavour to situate recent technological landmarks more properly in their historical niche; concluding, by foregrounding the computationally-impregnatable barriers which remain between ‘Deep Minds’ and `Real Minds`.