Organizations that collect large amounts of data from customers, citizens, or the environment are most likely to need big data management and analytical tools. This includes government agencies that maintain records (e.g. national crime databases), companies that track user behavior online (e.g. websites), and industrial organizations that collect sensor data (e.g. weather data for energy companies). These organizations generate huge volumes of structured and unstructured data that can provide valuable insights if analyzed properly.
Supercharging Smart Meter BIG DATA Analytics with Microsoft Azure Cloud- SRP ...Mike Rossi
Explosive growth of Smart Meter (SM) deployments has presented key infrastructure challenges across the utility industry. The huge volumes of smart meter data has led the industry to a tipping point which requires investments in modernizing existing data warehouses. Typical modernization efforts lead to huge capital expenditures for DW appliances and storage. Sizing this new infrastructure is tricky and can lead to underutilized or poorly performing hardware.
The Cloud is the catalyst to solving these Big Data challenges.
Utilizing a Cloud architecture delivers huge benefits by:
Maximizing use of existing architecture
Minimizing new CapEx expenditures
Lowering overall storage costs
Enabling scale on demand
What are big data in the contacts of energy & utilities, and how/where can the utilities find value in the data. In this C-level presentation we discussed the three prime areas: grid operations, smart metering and asset & workforce management. A section on cognitive computing for utilities have been omitted from the presentation due to confidentiality - but I tell you - it is mind-blowing perspectives on how IBM Watson will help utilities plan and optimize their operations in the near future!
See more on http://www.ibmbigdatahub.com/industry/energy-utilities
Stream Computing is an advanced analytic platform that allows user-developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of real-time sources. The solution can handle very high data throughput rates, up to millions of events or messages per second.
SMi Group is bringing to London this December, a new masterclass training course entitled Big Data for Utilities - combining and creating value from transactional, geospatial and real-time domain information. Don't miss this must attend course in association with Alliander and SAP UK & Ireland
Manufacturing Data Center Fast Facts: Big Data, Storage, Security & RecoveryInsight
Have you heard the phrase, “data is the lifeblood of business”? It’s especially true in the manufacturing space where data provides insight into everything from supply order placements to quality assurance. Explore how your business can benefit from modern data center solutions and best practices.
Learn more: http://ms.spr.ly/6007TZ2ZW
Supercharging Smart Meter BIG DATA Analytics with Microsoft Azure Cloud- SRP ...Mike Rossi
Explosive growth of Smart Meter (SM) deployments has presented key infrastructure challenges across the utility industry. The huge volumes of smart meter data has led the industry to a tipping point which requires investments in modernizing existing data warehouses. Typical modernization efforts lead to huge capital expenditures for DW appliances and storage. Sizing this new infrastructure is tricky and can lead to underutilized or poorly performing hardware.
The Cloud is the catalyst to solving these Big Data challenges.
Utilizing a Cloud architecture delivers huge benefits by:
Maximizing use of existing architecture
Minimizing new CapEx expenditures
Lowering overall storage costs
Enabling scale on demand
What are big data in the contacts of energy & utilities, and how/where can the utilities find value in the data. In this C-level presentation we discussed the three prime areas: grid operations, smart metering and asset & workforce management. A section on cognitive computing for utilities have been omitted from the presentation due to confidentiality - but I tell you - it is mind-blowing perspectives on how IBM Watson will help utilities plan and optimize their operations in the near future!
See more on http://www.ibmbigdatahub.com/industry/energy-utilities
Stream Computing is an advanced analytic platform that allows user-developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of real-time sources. The solution can handle very high data throughput rates, up to millions of events or messages per second.
SMi Group is bringing to London this December, a new masterclass training course entitled Big Data for Utilities - combining and creating value from transactional, geospatial and real-time domain information. Don't miss this must attend course in association with Alliander and SAP UK & Ireland
Manufacturing Data Center Fast Facts: Big Data, Storage, Security & RecoveryInsight
Have you heard the phrase, “data is the lifeblood of business”? It’s especially true in the manufacturing space where data provides insight into everything from supply order placements to quality assurance. Explore how your business can benefit from modern data center solutions and best practices.
Learn more: http://ms.spr.ly/6007TZ2ZW
CTO of ParStream Joerg Bienert hold a presentation on February 25, 2014 about Big Data for Business Users. He talked about several use cases of current ParStream customers and ParStreams' technology itself.
From grid infrastructure analytics to consumer analytics, the true power of data is starting to be realized. Greentech Media Co-Founder and President, Rick Thompson, sets the stage for the days presentations and panels.
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
Kainos Technology Sdn Bhd, a startup company in Malaysia since 2013. We are developing a product called MASTIS which is a facilities management solution for building maintenance services. This presentation is talk about how IoT technologies can be used in building facilities maintenance service industry.
Check out this white paper from eInfochips which showcases how energy and utility providers can unlock potential service opportunities using our predictive analytics solution across all stages of the business cycle. Major utility players are set to roll out millions of smart meters with the aim of generating actionable insights even though as per the industry’s own admission, any serious effort toward monetization is being offset by a lack of core IT capabilities, especially in big data technology. Capturing proactive intelligence on consumer behavior is the way to go. In this white paper, eInfochips demonstrates how utility players can predict demand response, generation response and create new revenue models around coincidental peak demands, smart expenditure modeling and other forms of end user data.
Conduit unleashes the power of your data by securely connecting data sources to the business intelligence tools you rely on in real time. Lightweight data virtualization has never been easier. Contact us for a FREE trial: Marketing@bpcs.com.
Digital Transformation: How to Run Best-in-Class IT Operations in a World of ...Precisely
IT leaders looking to move beyond reactive and ad hoc troubleshooting need to find the intersection of maintaining existing systems while still driving innovation - solving for the present while preparing for the future. Identifying ways to bring existing infrastructure and legacy systems into the modern world can create the business advantage you need.
View the conversation with Splunk’s Chief Technology Advocate, Andi Mann and Syncsort’s Chief Product Officer, David Hodgson where we discuss the digital transformation taking place in IT and how machine learning and AI are helping IT leaders create a more business-centric view of their world including:
• The importance of data sharing and collaboration between mainframe and distributed IT
• The value of integrating legacy data sources and existing infrastructure into the modern world
• Achieving an end to end view of IT operations and application performance with machine learning
In this presentation we will be discussing the business benefits for data centre power and environmental monitoring and practical steps you can take to reduce risk and increase efficiency. Richard May bio.: Richard May is the Data Centre Power SME and Country Manager for Raritan UKI and Nordics. With over 17 years’ data centre experience, specialising in rack monitoring, metering and control, Richard works to support Raritan customers and partners; helping to maximise the efficiency of their existing data centres, and developing strategies for their new facilities.
CTO of ParStream Joerg Bienert hold a presentation on February 25, 2014 about Big Data for Business Users. He talked about several use cases of current ParStream customers and ParStreams' technology itself.
From grid infrastructure analytics to consumer analytics, the true power of data is starting to be realized. Greentech Media Co-Founder and President, Rick Thompson, sets the stage for the days presentations and panels.
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
Kainos Technology Sdn Bhd, a startup company in Malaysia since 2013. We are developing a product called MASTIS which is a facilities management solution for building maintenance services. This presentation is talk about how IoT technologies can be used in building facilities maintenance service industry.
Check out this white paper from eInfochips which showcases how energy and utility providers can unlock potential service opportunities using our predictive analytics solution across all stages of the business cycle. Major utility players are set to roll out millions of smart meters with the aim of generating actionable insights even though as per the industry’s own admission, any serious effort toward monetization is being offset by a lack of core IT capabilities, especially in big data technology. Capturing proactive intelligence on consumer behavior is the way to go. In this white paper, eInfochips demonstrates how utility players can predict demand response, generation response and create new revenue models around coincidental peak demands, smart expenditure modeling and other forms of end user data.
Conduit unleashes the power of your data by securely connecting data sources to the business intelligence tools you rely on in real time. Lightweight data virtualization has never been easier. Contact us for a FREE trial: Marketing@bpcs.com.
Digital Transformation: How to Run Best-in-Class IT Operations in a World of ...Precisely
IT leaders looking to move beyond reactive and ad hoc troubleshooting need to find the intersection of maintaining existing systems while still driving innovation - solving for the present while preparing for the future. Identifying ways to bring existing infrastructure and legacy systems into the modern world can create the business advantage you need.
View the conversation with Splunk’s Chief Technology Advocate, Andi Mann and Syncsort’s Chief Product Officer, David Hodgson where we discuss the digital transformation taking place in IT and how machine learning and AI are helping IT leaders create a more business-centric view of their world including:
• The importance of data sharing and collaboration between mainframe and distributed IT
• The value of integrating legacy data sources and existing infrastructure into the modern world
• Achieving an end to end view of IT operations and application performance with machine learning
In this presentation we will be discussing the business benefits for data centre power and environmental monitoring and practical steps you can take to reduce risk and increase efficiency. Richard May bio.: Richard May is the Data Centre Power SME and Country Manager for Raritan UKI and Nordics. With over 17 years’ data centre experience, specialising in rack monitoring, metering and control, Richard works to support Raritan customers and partners; helping to maximise the efficiency of their existing data centres, and developing strategies for their new facilities.
Gain New Insights by Analyzing Machine Logs using Machine Data Analytics and BigInsights.
Half of Fortune 500 companies experience more than 80 hours of system down time annually. Spread evenly over a year, that amounts to approximately 13 minutes every day. As a consumer, the thought of online bank operations being inaccessible so frequently is disturbing. As a business owner, when systems go down, all processes come to a stop. Work in progress is destroyed and failure to meet SLA’s and contractual obligations can result in expensive fees, adverse publicity, and loss of current and potential future customers. Ultimately the inability to provide a reliable and stable system results in loss of $$$’s. While the failure of these systems is inevitable, the ability to timely predict failures and intercept them before they occur is now a requirement.
A possible solution to the problem can be found is in the huge volumes of diagnostic big data generated at hardware, firmware, middleware, application, storage and management layers indicating failures or errors. Machine analysis and understanding of this data is becoming an important part of debugging, performance analysis, root cause analysis and business analysis. In addition to preventing outages, machine data analysis can also provide insights for fraud detection, customer retention and other important use cases.
Data reply sneak peek: real time decision enginesconfluent
Events happen constantly in every business: a purchase in an online shop, a credit limit is hit, the mobile internet plan has been exhausted, users interact with a website. Events rule the business world. So why would you react to them hours or days later? Real-Time Decision Engines enable a variety of use cases, driving new products, increasing user experience, reducing costs and risks by reacting instantly to business events.
From personalized instantaneous marketing campaigns to reacting to user interactions, Real-Time is the key to open up a world of use cases that batch and scheduled processing cannot efficiently satisfy. In this talk, we are going to show some example use cases that Data Reply developed for some of its customers and how Real-Time Decision Engines had an impact on their businesses.
InfoSphere Streams is an advanced computing platform that can quickly ingest, analyze and correlate information as it arrives from thousands of real-time sources.
IT professionals are being asked to do more with less and highly skilled resources are in demand. As streaming applications play a growing role in critical applications so does the need for simplicity. InfoSphere Streams empowers IT users of all types and skill levels to have deeper insights into operations and performance. In today’s engaged world, a five minute delay means business goes elsewhere. A new administration console, a Java Management Extensions (JMX) management and monitoring application programming interface (API), simpler security and adoption of Apache Zookeeper are now available in InfoSphere Streams
Government, telecommunications, healthcare, energy and utilities, finance, insurance and automotive all have different challenges and requirements. However, all industries are facing unlimited potential to harvest all data, all the time. Stream Computing analyzes data in motion for immediate and accurate decision making
MongoDB World 2019: Data Digital DecouplingMongoDB
Why data decoupling? Learn how enterprises are pivoting to decouple big monolith and legacy data platform to smaller chunk and freedom to run anywhere and run multi-cloud agility for their business
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
7. 1. Describe the kinds of big data collected by the
organizations described in the case.
2. List and describe the business intelligence
technologies described in this case.
3. Why did the company described in this case need
to maintain and analyze big data? What business
benefits did they obtain?
8. Kind of Big
Data
Collected
Business Intelligent Technology
used
Business Benefit
Preserving
website for
historical
purposes
IBM Bigsheets
-a cloud application used to perform ad-
hoc analytics at web scale on
structured and unstructured content
-Help extract, annotate and visually
analyze vase amount of data and
delivering the result via a web browser
-Laverages Apache Hadoop
Framework and Map Reduce
Technology – help the organization to
handle huge quantities of data quickly
and efficiently and extract an useful
knowledge
Extract useful knowledge
from such huge data
which made responding
quickly and efficient to
user’s search and better
services to their user thus
increase customer
9.
10. Kind of Big Data
Collected
Business Intelligent
Technology used
Business Benefit
• Hidden patterns in
criminal activity
(correlation
between time,
opportunity and
organization) or
non-obvious
relationship
between individuals
and criminal
organizations
• criminal complaints
• National crime
records
• Public records
Real Time Crime Center
(RTCC)
•Centralized data hub that
rapidly mines information from
multiple crime databases and
disseminates that information
to officers in the field
•Crime Information
Warehouse - contain data
over 120 million criminal
complaints, 31 million national
crime record and 33 billion
public records
• Support for more
proactive policing tactics
by virtue of an ability to
see crime trends as they
are happening
• Faster and higher rate of
case-closing through
more efficient gathering
and analysis of crime-
related data.
• Improved overall data
integrity and speed of
data access to optimize
decision-making
11.
12. Kind of Big Data
Collected
Business Intelligent
Technology used
Business Benefit
• Location Data
• Wind Library –
stores nearly
2.8 petabytes
• 178 parameter
– barometric
pressure,
humidity, wind
direction,
temperature,
wind velocity,
other company
historical data
IBM InfoSphere BigInsights
running on IBM System x
iDataPlex Server
-Manage and analyze
weather and location data
- reduce the base resolution
of its wind data grid from
27x27 km area down to a
3x3 km (90% reduction) –
immediate insight into
potential location.
reducing data processing time
Quickly and accurately predict
weather patterns at potential
sites to increase turbine energy
production.
Save money – avoid from spent
on repairing and replacing
damaged turbine by the wind.
Save time – the company
forecast optimal turbine
placement in 15 minutes instead
of 3 week – enable customers to
achieve a return on investment
more quickly
13.
14. Kind of Big Data
Collected
Business Intelligent
Technology used
Business Benefit
• Customer
related
information
(Web surveys,
e-mails, text
messages,
website traffic
patterns, and
data location in
146 countries
Consumer Sentiment
Data
Storing data centralized
instead of within each
branch
• Reducing time spent
processing data
• Improving company response
time to customer feedback
• able to determine that delays
were occurring for returns in
Phildelphia during specific time
of the day
• Enhanced Hertz’s performance
and increased customer
satisfaction.
15. Meeting 3 – 11/05/2015
CASE 1 : BIG DATA, BIG REWARDS
Identify THREE DECISIONS that were improved by
using big data
22. Meeting 3 – 11/05/2015
CASE 1 : BIG DATA, BIG REWARDS
What KINDS OF ORGANIZATIONS are most likely to
need big data management and analytical tools? Why?
23. Organizations which responsible to score that huge information
such as national library, registration department, income tax,
banking institutions and so on because these organizations
typically be a sources for government and the public.
Authorities organization such a police department, custom,
immigration because they need to store a big data about criminals
and also public to use for safety of the society.
Organization need the big data to predict the weather and location
data, very useful for the companies to accurately make decision.
Thus Vestas needed the data about location and wind to locate
their turbines.
Editor's Notes
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.
Encourage open communication - employees express their ideas and perspectives without criticism.
Actively promote organizational effectiveness, reputation, values and ethics - Employees want to feel good about their leaders, where they work, the end products they made and the reputation of their company.
Culture -Encourage employees to find a personal fit with the company culture.
Incentives - Incentives that are matched to employee’s accountability and results. Allocated based on objective criteria and that different employees are motivated by different things.
Celebrate both financial and non-financial achievements - Employees need to feel validated and that they are a valued part of the organization.