Pre-Processing Big Data: Techniques to improve quality of big data analysis

IoT is a technology that has the potential to make us healthy, wealthy, and wise especially in healthcare. Healthcare is just now adopting IoT to improve patient outcomes and decrease the cost of care.

In this webinar, you’ll learn:

- How to identify if an IoT solution will work for your use case.
- What others in healthcare are using IoT for.
- The challenges of IoT in healthcare

Whenever there is data, there is the chance to visualize it and gain valuable insights that can drive change and improvements. Governments have realized the potential that data holds for transforming our towns, cities, living spaces and communities to better address the needs of our modern society.

Governments may want to change public transport services to suit commuters who move away from city centers due to increasing living costs, or develop programs that deliver more support services to areas showing high incidences of mental illnesses, or simply monitor bike traffic to assess the necessity of additional cycle lanes and bike share programs in our capitals. Data and data visualization can help us identify the needs of our communities and can support us in addressing them effectively.

In this webinar Andy and Eva will present examples of Government using data to improve services for communities and will share how you can get involved through analyzing open data and becoming part of the wider 'dataviz' community.

We will examine challenges regarding business model design in the emerging context of the Internet of Things (IoT).
An unrefined IoT business model implies a significant risk in terms of investment and implementation.

The key question is, "How can IoT application models be subjected to a reality check taking into account challenges pertaining technology, organization and target markets?"

Moving from A-B is slowly being revolutionised through data. Car-sharing and ride-hailing are just the beginning. Thousands of connected devices are currently monitoring data points, and although stand-alone analysis can be useful, true innovation occurs when these data sets are combined to transform into something new.

In the near future, IoT data explosion and the API revolution will collide to change city planning, urban movement and the role of the car in the 21st century.

First off, we set out to understand what big data means in the context of transportation, answering questions such as what is it, where is it coming from, and what can you do with it.
- Next, we'll zoom out and apply these learning to transport innovation in a wider context, considering how it will influence concepts such as urban movement, social mobility, and quality of life.
- Finally, we'll discuss the relationship between open data and innovation.

For decades “things” have been connected to the Internet. Embedded in carefully planned end-to-end solutions, the what and why of the data arising from these devices has often been hard-coded. In other words, in the M2M world, it is usually clear from the outset what is going to happen with the data. In a future IoT, this won’t necessarily be the case. In a world full of connected devices, the meaning and the potential of the device data is only going to become clear in the context where it is needed in.

But how can software tell that your connected thermometer is useful for a medical application, or that a car in the drive way is likely an indicator of your partner’s presence? This is where device catalogues, information models and ontologies come in handy.

While the talk is not specifically tailored towards a smart city focus, it should become clear how these technologies can be useful in such environment.

Fog computing represents a tectonic shift for the future of transaction management, distributed supply chain and overall experience. It blurs the lines between the edge and the cloud and puts the focus on the systems which manage and balance the delivery of coherent, end-to-end sessions and associated transaction level agreements. As a result, this new technology is pervasive in several industries.

Join this panel of experts as they discuss solutions with specific industry use cases from smart fog for Cities, Buildings, Ports, and Maritime.

Moderator: Katalin Walcott, Work Group Chair Manageability at OpenFog Consortium & Principal Engineer - IoT/Fog Computing Orchestration Architecture at Intel

Panelists:
- Jeff Fedders, President at OpenFog Consortium & Chief Strategist, IoTG Strategy and Technology Office at Intel
- Mark Dixon, Senior Architect for Smarter Cities at IBM
- Matthew Bailey, President, Powering IoT - Smart City advisor and strategist to governments, technology corporations, and economic development agencies

See how Netflix built its analytics in the cloud with Tableau and Amazon Web Services

Building out a data platform doesn't have to be like building a House of Cards, and our friends at Netflix know this better than anyone else. With 86 million members and counting, and more than 700 billion events per day, Netflix has had to expand their data capabilities by developing a scalable and flexible analytics platform built on Tableau and AWS.

Attend this webinar to hear from Albert Wong, analytics expert at Netflix, to see how they simplified their data stack by building a data lake/data warehouse strategy which allows Netflix to collect and store massive amounts of data, supporting thousands of Tableau users with managed data.

You'll learn about:

How to set up effective analytics on top of enormous data sets
How Netflix serves large groups of people with governed data
The details of Netflix's data lake/data warehouse strategy
How Netflix manages Hadoop with Tableau

Fog computing has the potential to resolve the issues with network latency since the media rich content can be delivered through such nodes directly.

Fog Computing inside the mobile network providers opens up a window of revenue opportunities for MNO's and creates a innovative space in content & application delivery platform.

Join this webinar to learn how to tackle the different challenges with fog computing and its role in the IoT cycle.

In this talk, Ram will provide a unified framework for Internet of Things, Cyber-Physical Systems, and Smart Networked Systems and Societies, and then discuss the role of ontologies for interoperability.

The Internet, which has spanned several networks in a wide variety of domains, is having a significant impact on every aspect of our lives. These networks are currently being extended to have significant sensing capabilities, with the evolution of the Internet of Things (IoT). With additional control, we are entering the era of Cyber-physical Systems (CPS). In the near future, the networks will go beyond physically linked computers to include multimodal-information from biological, cognitive, semantic, and social networks.

This paradigm shift will involve symbiotic networks of people (social networks), smart devices, and smartphones or mobile personal computing and communication devices that will form smart net-centric systems and societies (SNSS) or Internet of Everything. These devices – and the network -- will be constantly sensing, monitoring, interpreting, and controlling the environment.

A key technical challenge for realizing SNSS/IoE is that the network consists of things (both devices & humans) which are heterogeneous, yet need to be interoperable. In other words, devices and people need to interoperate in a seamless manner. This requires the development of standard terminologies (or ontologies) which capture the meaning and relations of objects and events. Creating and testing such terminologies will aid in effective recognition and reaction in a network-centric situation awareness environment.

Before joining the Software and Systems Division (his current position), Ram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Lab, where he conducted research on standards for interoperability of computer-aided design systems.

We are observing a monumental effort from the industry and academia to make everything connected. Naturally, to understand the needs of these connected things, we need a better understanding of humans and where, when, and how they interact. This behavioural understanding would help us to create digital services and capabilities that fundamentally change the way we experience our lives.

In this talk, I will explore the system and algorithmic challenges in modelling human behaviour. I will discuss how mobile and wearable devices together with the wireless network can be used as a multi-sensory computational platform to learn and infer human behaviour and to design user-centred connected services across Enterprise, Urban City and Lifestyle.

Dr Fahim Kawsar leads the Internet of Things research at Bell Labs and holds a Design United Professorship at TU Delft. His current research explores novel algorithms and system design techniques to build transformative multi-sensory systems for disruptive mobile, wearable and IoT services. He borrows tenets from Social Psychology, learns from Behavioural Economics and applies Computer Science methods to drive his research. He is a frequent keynote, panel and tutorial speaker, hold 15+ patents, organised and chaired numerous conferences, (co-)authored 100+ publications and had projects commissioned. He is a former Microsoft Research Fellow and has worked before at Nokia Research, and Lancaster University. His work and publications can be viewed at http://www.fahim-kawsar.net.

BigData requires processing performance but even more it requires agility of your cloud analytics. Iver will demonstrate how today's SAP Analytics has leading capabilities when used in a highly complex and dynamic environment accessing extreme data volumes.

Do you want to get actual knowledge from your data, to understand it and to predict what will happen next? We will see what it takes from the device to the dashboard.

In this webinar, we will discuss:
- Use cases of IoT Analytics in different areas.
- Architectural components & strategy required for a complete IoT solution.
- Application Example.

Big data analytics is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution. Thanks to the data deluge from millions of sensors from IoT networks, it is humanly impossible to analyse and make sense of the data from sensors without analytics tools and processes.

In this webinar, we will go over basics of big-data analytics, how analytics is different from traditional data warehouses or business intelligence systems, different tiers of data analytics etc., We will also see different use-cases of IoT from Smart Home to Transporation to Smart City context and how analytics can be applied for various use-cases for actionable insights.

Webinar also briefly touches upon machine learning tools / techniques that are available as-a-service on cloud today.

Apache Zeppelin is a great entry point for Data Scientist to explore and model Data.

In an enterprise environment, this exploration tool can be used to assemble pipeline of notes and deploy them in a production system.

In this webinar, you will learn how to:

+ Create functional notes corresponding to each step of the analysis.
+ Call a note from another note.
+ Pipe multiple notes together.
+ Create a deployable unit and run this unit on a remote cluster

Join Andy Kriebel and Eva Murray to hear about #MakeoverMonday, the popular social data project linking hundreds of members from the global data visualization community in an effort to create better charts and more useful data stories.

In this webinar Andy and Eva will share how Makeover Monday not only results in thousands of better data visualizations, but also helps people find their 'voice' in the community and land their dream jobs all while becoming better analysts and story tellers.

They will also discuss the challenge for week 20, present their own makeovers, and the design and thought process that went into them.

Join this webinar to learn:

1. What is Power BI?
a. More power to Business Inteligence

2. Why Power BI?
a. Analytics
b. Visualization

3. How?
a. Which data sources we can connect and analyse with Power BI?
b. How to connect those data sources to Power BI?
c. What is the role of R as a data source?
d. How to visualise and Analyse?
i. Design skills
ii. Tips and tricks
iii. Analytics patterns
1. Custom visuals
2. R Custom visuals (Predictive Analytics)

4. What about Backend Management?
a. Excel / Azure SQL / Azure Storage or Other
b. Custom Tables / Columns / Measures
i. What / Why / How?

5. Power BI Updates
a.Monthly Updates
b. Power BI Community for queries and request/issues updates
i. How to use this?

The webinar drives into the introduction of the architecture of Tensorflow and the designing of use case.

You will learn:
-What is an artificial neuron?
-What is Tensorflow? What are its advantages? What's it used for?
-Designing graphs in Tensorflow
-Tips & tricks for designing neural nets
-Use case