On the third Wednesday of each month Iasa will host a Virtual Conference that will run on a real-time schedule. This month’s eSummit, occurring March 16th, features highly recognized subject matter experts in Big Data/Information Architecture. The eSummit will have a delayed archive available for one year.
Interactive webcasts are offered in real-time, while presenter show visuals such as PowerPoint slides and desktop applications. Participants will have the opportunity to interact with the presenters in real time. See below for the upcoming speakers and topics.
Topic Listing
Presentation (click for abstract) | Speaker | Time |
---|---|---|
Scalable Database Architecture For SaaS Solution (Microsoft Azure Perspective) | Srinivasan Sundara Rajan | 7:00 AM |
Deep Learning for the masses | Samuel Cozannet | 8:00 AM |
Fast Data – the New Big Data | Peter Vescuso | 9:00 AM |
Big Data Open Architecture – A Jump Start to the Realization Phase | Ahmed Aamer | 10:00 AM |
Building an Advanced Analytics Capability | Tilak Mitra | 11:00 AM |
Turning Big Data into Big Understanding with Information Architecture | Dan Klyn | 12:00 PM |
The Secret Sauce behind the Most Successful Big Data Strategies | Justin Lokitz | 1:00 PM |
Tools on your Data Lake | Taposh Dutta-Roy | 2:00 PM |
Personalization and Recommendation with Big Data and Hadoop | Pranab Ghosh | 3:00 PM |
Big Data Platform : Improve Your Odds with Predictability | Bhagvan Kommadi | 4:00 PM |
TBD
Fast Data – the New Big Data
The data you need to manage isn’t getting smaller, or slower. It’s a snowball, compounding in both speed and volume.
If you’re building applications on fast, streaming data, you need to analyze it, gain insight and take action on it now, not at the end of a batch job.
Fast data is streaming data or data in motion – and it creates Big Data. Forrester analyst Mike Gualtieri thinks the perishable insights in fast data “can have exponentially more value than after-the-fact traditional historical analytics.” So how to tap it and why would you use the same infrastructure to handle fast data the way you handle big data?
Many approaches used to manage fast data have challenges:
- Batch processing – if your data is handled in batches, even micro batches, actions taken on that data can be too late
- Eventual consistency – sacrificing data consistency can lead to errors and problems such as under/over billing, or under/over budget or resource use
- Integrating a collection of moving parts – trying to build a solution with individual components can take more code, more time, and more expertise than you bargained for, and results in a more complex, less reliable (and hard to manage) solution
What does work? An in-memory database that supports actions and streaming analytics in real-time without sacrificing transactional integrity, performance, and scale.
Tune in to our presentation to hear more and see the lessons learned from an actual real fast data use case.
Big Data Platform : Improve Your Odds with Predictability
Big Data platform has discovery and prediction consists of Clustering, Outlier detection and affinity analysis. Clustering is detecting natural groupings. Outlier detection is detecting anomalies. Affinity analysis is identifying co-occurrence patterns. Classification, Regression, Recommendation is part of Prediction process. Classification is predicting categories. Regression is predicting value. Recommendation is predicting preferences.Enterprises are focussing on big data initiatives towards tactical business objectives, product information management, performance management, business execution correction, innovation through new products and predictive capabilities.
Big Data Open Architecture - A Jump Start to the Realization Phase
This session will explore the momentum required for the large organizations to explore and realize the value through the adoption and implementation of Business Analytics and Data Governance by orchestrating an Open Data Enterprise Architecture. We shall discover the analysis required for the Data Engineering platforms, Architectures, Methodologies, and Frameworks to manage the exponential increment of data along with the inherited architectural complexities for the infrastructure systems to handle the computational power required by the large datasets for effective and accurate analysis.
- Envisioning and Readiness Matrix
- Big Data Open Infrastructure
- Align, Improve, and Integrate
- Mapping, and Matching
- Data and Business Patterns and Anti-Patterns
The Secret Sauce behind the Most Successful Big Data Strategies
Innovative, sustainable Big Data Business Models are as pervasive and sought after as they are elusive. For every startup that designs and implements what amounts to a simple and effective big data business model (see any social network), perhaps changing the entire landscape with it, there are literally hundreds (if not thousands) of larger, more mature companies looking for ways to monetize their own big data in the hope that they can capture new revenue streams (and compete effectively in the future). So, what’s the secret to successful big data business models and strategies? How might you develop a big data strategy for your company? In this webinar Justin Lokitz will highlight and unpack the most popular big data business models and strategies based and related value propositions. He will also discuss the process by which you can design big data business models and value propositions for your company.
Scalable Database Architecture For SaaS Solution (Microsoft Azure Perspective)
Data holds key for the success of many SaaS solutions. Mainly as the application logic remain the constant, it is the Tenant specific data that makes the difference. In this context, this presentation addresses some of the issues associated with the Database Design and scalability for the SaaS Solutions.
To make the reference easier, specific implementation examples are given from Microsoft Azure (which is one of the leading Cloud Platform for hosting SaaS solutions).
However in the benefit of diversified enterprise audience, this presentation does not give any specific recommendation about the respective cloud platforms like AWS, AZURE or BLUEMIX rather let the enterprises utilize their own evaluation mechanism.
Turning Big Data into Big Understanding with Information Architecture
A key breakthrough in data transmission and storage in the late 1940s was the decoupling of information from meaning. Today, meaning is the proverbial “holy grail” with regard to what’s called Big Data. Whether or not there are needles of insight in the haystacks of raw information depends an awful lot on what we mean by meaning. Learn three strategies for working with and intensifying meaning, and the information architectural processes required to turn Big Data into Big Understanding with Dan Klyn from TUG.
Tools on your Data Lake
Today’s business users need better data and tools for operational reporting and advanced analytics. Data Lake, a next-generation data storage and management solution, was developed to meet the ever-evolving needs of increasingly savvy users. Depending on the industry, data lake can be on premise or in an external cloud. Advanced analytics specially predictive and prescriptive are very essential for businesses. In this talk we will explore the tools needed on your data lake for on premise solutions.
Deep Learning for the masses
Deep Learning is hard. So hard that unless you are one of the GAFAs, you are probably stuck with running science experiments on a consumer grade video card. This prevents the next biggest revolution in software to happen.
Using application modelling, cloud technologies and big data, Canonical is creating a DeepStack: a reference application model for deep learning that anyone will be able to deploy, use and consume. In this talk, we will explain the background of this idea, where we currently stand, and discuss a use cases.
Building an Analytics Capability
Personalization and Recommendation with Big Data and Hadoop
This is where personalization recommendation engines come into the picture. They provide personalized recommendation based on the user’s behavior and the behavior of other like-minded users.
Meet our Speakers
Click image for more details
TBD
Ahmed Aamer
Ahmed Aamer is a Technology Evangelist and International Speaker with more than two decades of experience in Project Management, ERP, Application Development, e-Healthcare, Business Alignments & Transformations. He has delivered wealth of projects for different business domains across the globe. Has the capability to Design, Develop and Implement Data Monitoring Solutions through Big Data Operations Architecture. He has been designing & developing complete end-to-end managed solutions for Global customers with the primary role to Lead, Manage, Architect, Design, Develop & Implement Business solutions for various business segments and sectors. He has implemented Tens of e-Health solutions using the healthcare standards.
He has been actively delivering many high profile conferences, summits and symposiums across several countries. The addressed conferences were focused on Emerging Technologies such as Big Data, Cloud, and Digital Transformational technologies with customer centric orientation.
Bhagven Kommadi
Justin Lokitz
With 15+ years of experience of managing products and business model strategies for large, multi-national corporations, like Autodesk and Oracle, as well as small start-ups, Justin leverages his experience across a wide range of industry sectors to help large companies think, innovate and design more like start-ups, while helping start-ups find sustainable business models. Whether he is helping teams innovate, scale new products, or create sustainable strategies for the future, Justin does so by making strategy design an engaging experience.
Justin holds a BA in Environmental Science and Geography, from University of California Santa Barbara, a MBA in Design Strategy, from California College of the Arts, as well as professional certifications in software development and product management, from University of California Berkeley..
Peter Vescuso
Srinivasan Sundara Rajan
Srinivasan Sundara Rajan has 22 Years of Enterprise IT experience. His expertise lies in Social, Mobility, Analytics and Cloud Computing. He develops solutions that are futuristic in nature and in alignment with industry analysts.
He is a seasoned enterprise IT expert, mainly in the areas of solution, integration and architecture, across structured, unstructured data sources. His latest work involves Natural Language Processing, Semantic Enrichment of Unstructured Data, Data Mining and Predictive Analytics. He has a strong handle on all tiers of the enterprise IT spectrum and is geared to manage the massive flow of data from Internet of Things (IoT) with appropriate platform, tools and processes. Mr. Sundararajan is passionate about technical blogging. He is ranked as one of the top bloggers in the technology space and has a strong follower base.
Dan Klyn
In April 2016, Klyn begins serving a 2-year term as President of the IA Institute.
Taposh Dutta-Roy
Taposh Dutta-Roy is a technical executive and start-up advisor with a passion for turning data into actionable insights, meaningful stories and awesome products. He has a unique combination of products, technology, strategy, data science and start-up experience. He is consumer focused, machine learning and data science geek. He currently works at Kaiser Permanente and leads data science and innovation. He has experience in in a variety of tools and technologies that can be used in Big Data.
You can fork his code on github : https://github.com/taposh/
Samuel Cozannet
Follow Samuel on Twitter (@SaMnCo_23)
Tilak Mitra
As the CTO, Tilak not only drives IBM’s technical strategy around the strategic solutions portfolio but also drives transformative changes in IBM’s top clients either by innovating new business models or by assisting them in developing their IT transformational programs. His unique and deep skills in various frontiers of technology position him well to continuously straddle the fine line between business and IT.
Prior to joining IBM, Tilak was a Senior Software Engineer at Wipro, responsible for design and
development of a core module of a document management system product.
He has authored two books on SOA and SOA Governance and is credited with 25 journal
publications. He currently holds three patents and one innovation.
Follow Samuel on Twitter (@SaMnCo_23)
Pranab Ghosh
Big Data and Data Science Consultant, Open Source Project Owner, Blogger, Graduate of IIT, MIT and UC, 25+ years in Software Industry
- Have worked with myriad of technologies and platforms including main frames, real time and systems programming, java and enterprise applications, big data and cloud technologies.
- Experienced with Hadoop, Hive, Storm, Spark, NOSQL databases and the surrounding big data ecosystem
- Worked and consulted for Oracle, HP, Yahoo, Motorola, Apple, Accenture, Verizon and many startups and mid size companies.
- Owner of several big data open source projects, some of them being on scalable Machine Learning
- Active blogger covering topics around big data and cloud.
- Interested in Distributed Computation, Big Data, NOSQL DB and Machine Learning
Follow Samuel on Twitter (@SaMnCo_23)
Call For Speakers
Call for speakers and content for our next event
We are looking for thought leaders, and subject matter experts like yourself to grow our content. Your contributions would provide Iasa’s members and outside practitioners with a learning venue where they can share similar goals, interests, problems, and approaches within the IT Architecture domain.
Are you working on an exciting, original or innovative project? Have you created some neat technology or discovered a useful practice? Did you and your team, crack a mind-boggling engineering challenge?
If the answer to any of these questions is yes, we would love it if you would share your skills, experience and ideas in a talk contact us. Visit our contribution page!
April’s Topic: Business Architecture 2.0