The SpotDy City Pulse™ is built on top of cutting edge big data technologies along with deep data science and AI algorithms, for Financials to deliver right actions at right place at right time.
SpotDy BigAITM introduce a completely new model for building operational intelligence, giving companies a competitive edge by put all their data to work to uncover new insights in timely fashion without friction.
Learn about Addressing Storage Challenges to Support Business Analytics and Big Data Workloads and how Storage teams, IT executives, and business users will benefit by recognizing that deploying appropriate storage infrastructure to support a wide range of business analytics workloads will require constant evaluation and willingness to adjust the infrastructure as needed. For more information on IBM Storage Systems, visit http://ibm.co/LIg7gk.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
There is a great deal of discussion about the potential of “big data,” the high-volume, high-variety information assets that require new forms of data processing to enable companies to make better decisions and operate more efficiently. There is, however, one important caveat. Many companies—probably most—work in relatively sparse data environments, without access to the abundant information needed for advanced analytics and data mining. Companies that only have access to “little data” can still use that information to improve their business.
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
Learn about Addressing Storage Challenges to Support Business Analytics and Big Data Workloads and how Storage teams, IT executives, and business users will benefit by recognizing that deploying appropriate storage infrastructure to support a wide range of business analytics workloads will require constant evaluation and willingness to adjust the infrastructure as needed. For more information on IBM Storage Systems, visit http://ibm.co/LIg7gk.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
There is a great deal of discussion about the potential of “big data,” the high-volume, high-variety information assets that require new forms of data processing to enable companies to make better decisions and operate more efficiently. There is, however, one important caveat. Many companies—probably most—work in relatively sparse data environments, without access to the abundant information needed for advanced analytics and data mining. Companies that only have access to “little data” can still use that information to improve their business.
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
This talk is an introduction to Data Science. It explains Data Science from two perspectives - as a profession and as a descipline. While covering the benefits of Data Science for business, It explaints how to get started for embracing data science in business.
BIG DATA is having an enormous impact on the profile of workforces around the world. If you've ever seen the technology and experienced the impact it has on the pace of innovation in a business then the predictations made by McKinsey Global Institute will come as no surprise ( and just in case you've been on holiday for around two years, McKinsey is suggesting that by 2018 the US will face a shortfall of close to 200,000 analysts and 1.5 million managers with the right skills. In this presentation I outline the impact of BIG DATA on workforce design. I hope you find it informative and fun to read. Ian.
We conducted a ground-breaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
As firms move from siloed, transaction-oriented systems to more integrated,
socially aware ones, they will face challenges related to customer data. “Big data”
is characterized by increases in data volume, velocity, variety, and variability. To
improve customer engagement, companies must invest in solutions to effectively
manage big data.
Semantic 'Radar' Steers Users to Insights in the Data LakeCognizant
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
Investing in AI: Moving Along the Digital Maturity CurveCognizant
Digitally mature businesses are more likely to consider themselves at an advanced stage of AI adoption, according to our recent study, enabling them to turn data into insights at the scale and precision required today.
Solving The Data Growth Crisis: Solix Big Data SuiteLindaWatson19
Today’s Chief Information Officer operates in a perfect storm of data growth. Left unchecked data growth negatively impacts application performance, compliance goals and IT costs. Yet, this very same data is the lifeblood of today’s organizations. .
Why Is Data Literacy Important For Any Business?Bernard Marr
The more data literate your organisation is, the better your results will be. In my work with companies all over the world, I see it every day that organisations that fail to boost data literacy of their employees will be left behind because they are not be able to fully use the vital business resource of data to their business advantage. In this post, I explore what data literacy is, why it's crucial for every business and ways to promote data literacy.
This talk is an introduction to Data Science. It explains Data Science from two perspectives - as a profession and as a descipline. While covering the benefits of Data Science for business, It explaints how to get started for embracing data science in business.
BIG DATA is having an enormous impact on the profile of workforces around the world. If you've ever seen the technology and experienced the impact it has on the pace of innovation in a business then the predictations made by McKinsey Global Institute will come as no surprise ( and just in case you've been on holiday for around two years, McKinsey is suggesting that by 2018 the US will face a shortfall of close to 200,000 analysts and 1.5 million managers with the right skills. In this presentation I outline the impact of BIG DATA on workforce design. I hope you find it informative and fun to read. Ian.
We conducted a ground-breaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
As firms move from siloed, transaction-oriented systems to more integrated,
socially aware ones, they will face challenges related to customer data. “Big data”
is characterized by increases in data volume, velocity, variety, and variability. To
improve customer engagement, companies must invest in solutions to effectively
manage big data.
Semantic 'Radar' Steers Users to Insights in the Data LakeCognizant
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
Investing in AI: Moving Along the Digital Maturity CurveCognizant
Digitally mature businesses are more likely to consider themselves at an advanced stage of AI adoption, according to our recent study, enabling them to turn data into insights at the scale and precision required today.
Solving The Data Growth Crisis: Solix Big Data SuiteLindaWatson19
Today’s Chief Information Officer operates in a perfect storm of data growth. Left unchecked data growth negatively impacts application performance, compliance goals and IT costs. Yet, this very same data is the lifeblood of today’s organizations. .
Why Is Data Literacy Important For Any Business?Bernard Marr
The more data literate your organisation is, the better your results will be. In my work with companies all over the world, I see it every day that organisations that fail to boost data literacy of their employees will be left behind because they are not be able to fully use the vital business resource of data to their business advantage. In this post, I explore what data literacy is, why it's crucial for every business and ways to promote data literacy.
How Do You Improve Data Skills and Data Literacy in your Business?Bernard Marr
Data literacy should be a priority for every organization. Investing in data skills and data literacy is critical for all companies today. Most companies have a deficit in data skills that should be addressed as quickly as possible. There are several ways to improve data skills and data literacy in your business.
Big Data, Big Thinking: Untapped OpportunitiesSAP Technology
In this webinar factsheet, SAP’s Rohit Nagarajan and Suni Verma from Ernst & Young explore Big Data in India, adoption patterns across the globe, and how you can embark on your own Big Data journey.
Companies from across sectors are experiencing exponential growth in data as social interactions, rich media and a variety of devices generate new content. A tidal wave... of digital data is getting created through emails, instant messaging, survey videos, images, RFID tags, web text, blogs, geo-location devices, collaboration platforms like Twitter and Facebook, and so many other sources.
Business Intelligence is more than a fad. But to embrace it requires a significant commitment.
Every competitive business recognizes the power in knowledge. The definition of “knowledge” is both subjective and obscure. All too often, a business is unable to succinctly express what information it wants and what it will do with this information. Many earnest efforts are made to develop effective data reporting resources. The most common mistakes are costly, time consuming and wasteful.
Data set Improve your business with your own business dataData-Set
The objective of this module is to gain an overview of how to use the data you already have available in order to improve your business.
Upon completion of this module you will:
-Gain an understanding of how to take advantage of the existing data you already have
-Comprehend the location of where internal data already lies within your company
-Improve your knowledge on how data can help build your brand
Big & Fast Data: The Democratization of InformationCapgemini
Moving from the Enterprise Data Warehouse to the Business Data Lake
Is it possible that ubiquitous analytics represents the next phase of the information age? New business models are emerging, enabled by big data that business leaders are eager to adopt in order to gain advantage and mitigate disruption from start-ups and parallel industries. The winners are likely to be those that master a cultural shift as well as a technology evolution.
Our view is this will be realized through the alignment of a business-centric big data strategy, combined with democratization of the analytical tools, platforms and data lakes that will enable business stakeholders to create, industrialize and integrate insights into their business processes.
Innovative approaches are needed to free up data from silos whilst encouraging both the sharing and the continuous improvement of insights across the business. While it will be evolution for some, revolution for others; the risk of status quo is not just the loss of opportunity but also a widening gap between business and the internal technology functions.
https://www.capgemini.com/thought-leadership/big-fast-data-the-democratization-of-information
The objective of this module is to gain an overview of how to use the data you already have available in order to improve your business.
Upon completion of this module you will:
Gain an understanding of how to take advantage of the existing data you already have
Comprehend the location of where internal data already lies within your company
Improve your knowledge on how data can help build your brand
Data has become a key focus for corporate leaders today. Chartered Global Management Accountant (CGMA) designation holders are well placed to help translate data into commercial insights and value.
The Fast Fish Forum is an opportunity for challengers of convention and drivers of progress to come together for the benefit of South African business and society. The forum consists of purposeful, committed and open-minded people across industries, organisations and roles who collaborate and learn together; creating a critical mass that drives innovative change in our country.
At the second event, held at the BSG offices on 16 November 2016, we discussed two highly topical subjects:
1. Enhancing customer value using big data and actionable insights.
2. Driving innovation through customer insights.
To find out more and join the conversation follow us @FastFishForum and http://bit.ly/fastfishforum.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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
2.
INTRODUCTION
In digital era of this century, some firms use their limited resources effectively &
efficiently and emerge as winners! How? They generate useful insights by
analysing both structured and unstructured data together irrespective of volume,
velocity and variety of the data.
Processing increasing volumes of data in a timely manner has become a challenge for financial
companies. Traditional BI approaches often fail to capture actionable information at right time due to
inherent limitations. First, it can take a great deal of time to collect, prepare, and analyze all of your
fragmented and often unstructured data. Second, most lineofbusiness professionals have to rely on
IT to gather the data and organize it in a data warehouse – a prerequisite for using traditional business
intelligence. And often, by the time the data is ready, the business needs have changed or it’s too late
to aid in decision making. Third, processing unstructured data from variety of data sources poses
challenge using traditional data warehousing technologies. Data warehousing applications are mostly
designed to handle structured and limits the ability to analyse the data beyond descriptive analytics.
And finally, traditional BI technologies doesn’t effectively use data science technologies and thus
limiting predictive insights and impact on overall value chain. Data science maps all of the relevant
data, regardless of volume, variety and velocity, into a coherent model to derive meaningful predictive
analytics.
It is clear unless data is getting transformed into impactful decisions in real time, it is a complete
waste of resources and time. Financial firms need to move beyond traditional data warehousing
techniques to be able to generate useful and timely insights
The numbers tell the story:
● The Big Data market is at $5.1 billion in 2014 and is expected to grow to $32.1 billion by
2015—and to $53.4 billion by 2017.
● We create 2.5 quintillion bytes of data daily; 90% of the data in the world today has been
created in the last two years alone.
● 62% of companies believe that Big Data has significant potential to create competitive
advantage.
6.
Customer Analytics
Customer Profiling
In financial services understanding the customer is a key for sales and marketing campaigns. Financial
services collect variety of data such as customer transactions, social and online buying habits. Turning
this big data into deeper, datadriven customer insights are critical to tackling challenges like improving
customer conversion rates, personalizing campaigns to increase revenue and lowering customer
acquisition costs
SpotDy BigAITM
big data and analytics platform enables financial services companies analyzing all of
the data available about their customers and group customers into different segments based on their
expectations and banking needs. With accurate and uptodate customer segmentation, banks and
financial services companies can grow their customer base and increase business.
Benefits include :
● Identify the characteristics to profile and segment customers real time.
● Analyze historical data from both inside and outside (Social, Web etc) the financial
services to understand the customer trends.
● Grouping customers based on demographics, age group, geography and social media
preferences, firms can launch targeted smart campaigns.
● Visualize the segment patterns in real time so that financial services can build marketing
campaigns driven by data.
figure: benefits of Customer Analytics
7.
Personalized product offerings
Retail banks have vast amounts of customer data – from Internet data to customer transaction data to
social media data (both inside and outside). The challenge is to figure out how to use this data to
understand for customer trends on individual basis that can support marketing campaigns and
personalized product and service offerings.
SpotDy BigAITM
big data and analytics platform enables financial services companies to target new
product and service offerings to the right customers through deep analyzing customer buying habits,
what channels the customer listens to, and who the key influencers are in timely manner.
Benefits include :
● Predicting what new products customers will purchase from the bank, and when
● Creating targeted marketing campaigns to segmented customers
● Identify customer risk profile, demographics, existing buying patterns and match these
criteria to existing card offerings and market right card products.
● Visualize the campaign tracking so that financial services can dynamically optimize the
campaigns driven by data.
figure: benefits of personalization services
9.
New Products & Services
Innovation with introduction of new products and services is essential for survival in this global
competitive markets. Understanding customer preferences, customer behavior, customer usage of
existing products and services helps firms to come up with new products & services. Combining
inhouse data with social data and marketing data using SpotDy’s analytics platform can generate
insights using for firms
SpotDy BigAITM
big data and analytics platform enables financial services to understand existing
products and services better from customer standpoint using both inside and outside (Social, Web
etc) to identify new product and services opportunities
Key Benefits include :
● Identify existing products and services usage patterns, most heavily used pages, use
cases and customer pain points
● Identify potential scenarios to streamline existing products to provide better customer
experience
● Come up with new product and service ideas from data insights
figure: benefits of product innovation
10.
Brand Analytics
A brand is sum of all the feelings, thoughts, and recognitions positive and negative that people in the
the target audience have about a company , a product or a service. Financial companies spend
millions of dollars annually to elevate perception of brand in people’s minds. Often times, its not easy
of qualitatively measure the metrics associated with the brand to identify the brand value without
proper analytical tools.
SpotDy BigAITM
big data and analytics platform enables financial services to analyze the company’s
structured data and social media(unstructured data) measure brand analytics and thus zoom in to
effectiveness of brand promotion activities. with proper data insights, these financial companies can
effectively use the marketing budget and invest resources in the right channels to increase brand
awareness.
Benefits include:
● measure key brand analytics metrics such as new vs returning users, visitor loyalty &
recency, brand lift(likelihood of target action),
● Identify and measure traffic from discussion forums/communities and understand how
much brand is talked about in general forums
● measure search share to understand how many people would prefer your brand when
compared to competitors, effectiveness of brand promotion activities when compared to
competitor traffic
figure: benefits of Brand Analytics
11.
SpotDy BigAITM
Framework for Big Data Analytics
With the explosion of volume, velocity and variety of data, traditional approaches for collecting and
processing data have inherent limitations that impact the ability to make informed and timely decisions.
SpotDy BigAI™ Platform products introduces a completely new model for developers and analytics
using deep data science, giving companies a competitive edge by uncovering new insights in real time.
With SpotDy BigAI™, enterprises don't need data scientists and big data teams, instead they need a
platform which empowers to build smart analytics. SpotDy BigAI™ has builtin machine learning
algorithms to distill actionable insights from very large datasets. By taking the analysefirst approach,
SpotDy BigAI™ eliminates the need to spend millions on storage and eschews the time constraints to
store, process and serve data.
SpotDy BigAI™ Web Services platform
12.
Features of BigAI™ WebServices™
Data Integration
SpotDy BigAI™ Connectors is designed for efficiently to
load data into BigAI™ platform. BigAI™ Connectors
supports fetching data from various sources like social,
structure, JDBC, Web, Object stores like S3 and
integrate with BigAI platform as easy as following a
wizard. Say goodbye to ETL and defined schemas.
Data Processing
SpotDy BigAI™ is world’s first big data science platform.
SpotDy BigAI™ offers wide variety data science
solutions and powers applications and business process
to make effective decisions in real time.
SpotDy BigAI™ batch, stream and query engines is
ideal for building operational intelligence directly into
your applications or offline analytics. This flexibility and
ease of use makes SpotDy BigAI™ the ideal platform for
building big data applications.
Big Data Visualization
SpotDy BigAI™ Dynamic Visualization provides you with
a blank HTML5 canvas to design beautiful infographics
or reports that will automatically update every time the
data is updated. The builtin collaboration platform
enables you to share charts on social platforms, email
and messaging. Even better your visualizations are
consumable on any device.
API Endpoint
API Endpoint will bridge the chasm between data and
delivery. API Endpoint is a purposebuilt platform that
provides everything to manage data and deliver right to
your applications. API Endpoint provide services to
measure the success of your API program with
endtoend analytics.