Gain Competitive Advantage by Increasing Knowledge Productivity: Link Insights from Big Data directly to Business Processes
• real-time monitoring of Big and Smart Data
• consolidated analysis of external (Web, Social Media, Deep Web, …) and internal (SharePoint, File Shares, Data Warehouses, …) data
• provision of direct business process support through dashboards and alerts
This presentation was held at the 2014 International Competitive Intelligence Conference in Bad Nauheim, Germany.
CID and Predictive Policing at the 2015 European Police Congress in BerlinCID GmbH
Today, Predictive Policing often refers to the analysis of big, structured data. The addition of unstructured information such as situation and field reports, filed charges, case information, and more means a powerful extension of knowledge and predictive analytics capabilities.
This presentation was held during a panel discussion on Predictive Policing at the 2015 European Police Congress in Berlin, Germany.
Competitive Intelligence & “Big Data“ – Information Monitoring, Analysis & Trend Detection in Real-Time
> how competitive intelligence can profit from knowledge Management & big data
> how to tackle information overload and analyze most different kinds of data from financial and market figures,
competitor and product information, news, scientific publications to social Media etc.
> possibilities and methods not only to manage knowledge but to gain insights and support decision making
> ways to prove the benefit of an investment in a ci tool for business
This presentation was held during the 2013 CiMi.CON Evolution Conference in Berlin, Germany
Analytics, Business Intelligence, and Data Science - What's the Progression?DATAVERSITY
Data analysis can include looking back at historical data, understanding what an organization currently has, and even looking forward to predictions of the future. This presentation will talk about the differences between analytics, business intelligence, and data science, as well as the differences in architecture — and possibly even organization maturity — that make each successful.
Learn more about these topics we will explore including:
Defining analytics, business intelligence, and data science
Differences in architecture
When to use analytics, business intelligence, or data science
Whether there has been an evolution between analytics, business intelligence, and data science
CID and Predictive Policing at the 2015 European Police Congress in BerlinCID GmbH
Today, Predictive Policing often refers to the analysis of big, structured data. The addition of unstructured information such as situation and field reports, filed charges, case information, and more means a powerful extension of knowledge and predictive analytics capabilities.
This presentation was held during a panel discussion on Predictive Policing at the 2015 European Police Congress in Berlin, Germany.
Competitive Intelligence & “Big Data“ – Information Monitoring, Analysis & Trend Detection in Real-Time
> how competitive intelligence can profit from knowledge Management & big data
> how to tackle information overload and analyze most different kinds of data from financial and market figures,
competitor and product information, news, scientific publications to social Media etc.
> possibilities and methods not only to manage knowledge but to gain insights and support decision making
> ways to prove the benefit of an investment in a ci tool for business
This presentation was held during the 2013 CiMi.CON Evolution Conference in Berlin, Germany
Analytics, Business Intelligence, and Data Science - What's the Progression?DATAVERSITY
Data analysis can include looking back at historical data, understanding what an organization currently has, and even looking forward to predictions of the future. This presentation will talk about the differences between analytics, business intelligence, and data science, as well as the differences in architecture — and possibly even organization maturity — that make each successful.
Learn more about these topics we will explore including:
Defining analytics, business intelligence, and data science
Differences in architecture
When to use analytics, business intelligence, or data science
Whether there has been an evolution between analytics, business intelligence, and data science
Learn about the emerging field of big data and advanced quantitative models and how the Rady School's MS in Business Analytics program is designed to solve important business problems.
Data-Ed Webinar: Monetizing Data Management - Show Me the MoneyDATAVERSITY
Practicality and profitability may share a page in the dictionary, but incorporating both into a data management plan can prove challenging. Many data professionals struggle to demonstrate tangible returns on data management investments, especially in industries such as healthcare where financial results aren’t necessarily an organization’s primary concern. The key to “monetizing” data management, therefore, is thinking about data in a different way: as an information solution rather than simply an IT one, using data to drive decision-making towards increased profits and potentially alternative returns on investment or value outcomes as well. Taking a broader view of data assets facilitates easier sharing of information across organizational silos, and allows for a wider understanding of the investment’s requirements and benefits.
In this webinar—designed to appeal to both business and IT attendees—your presenter will:
Describe multiple types of value produced through data-centric development and management practices
Expand on and beyond metrics meant for increasing revenues or decreasing costs—i.e. investments that directly impact an organization’s financial position
Detail how alternative statistics and valuations can be used to justify data management and quality initiatives
Data Analytics: An On-Ramp to a Better Understanding of Your BusinessSkoda Minotti
Data analytics is a hot topic in business today. But is it right for your business? What does it do for you, and most importantly, how do you get started? This executive overview explores the business implications of data analytics, while leaving the technicalities to the side.
Focus on Your Analysis, Not Your SQL CodeDATAVERSITY
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions.
Join us to learn how self-service data analytics allows analysts to:
- Utilize a drag-and-drop workflow for data and analytic processes without writing code
- Minimize data movement and ensure data integrity through in-database capabilities
- Easily work across relational and non-relational databases to deliver faster business results
Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
Advanced Analytics Governance - Effective Model Management and StewardshipDATAVERSITY
There’s been a shift toward digital business transformation with growing use of a broad spectrum of analytical capabilities (descriptive, diagnostic, predictive, prescriptive) to drive decision-making. Having a framework and overarching strategy for analytics governance is essential for data-driven organizations. Today’s advanced analytics and Business Intelligence (BI) professionals understand driving successful governance is critical for developing consistent, trusted, transparent, and effectively utilized analytics.
Join this webinar to learn best practices and vetted approaches for how to:
Ensure analytics governance is integrated with existing Data Governance processes, policies, operating model management, and Data Stewardship
Adapt governance best practices for different analytics use cases
Confirm alignment of your analytics and BI strategy with critical business objectives
Balance the rewards of digital technology and applied analytics with the compliance risks of new ethical rules, standards, and regulations
How Can You Calculate the Cost of Your Data?DATAVERSITY
Today, self-service, Cloud and big data technologies make new data preparation capabilities necessary…and possible. But, we've all been through the hype cycle and know the trough of disillusionment can come on hard and fast.
Organizations have been trying to solve the data quality problem and democratize insights for years spending millions of dollars and dedicating an increasing amount of resources to manage and govern the data. The result? Everyone is still looking to solve the problem.
Data preparation offers a new paradigm, but how can you avoid another round of minimal business impact? We’ll review a true data ROI model that helps organizations understand the value of existing versus modern data management architectures.
Implementing Big Data, NoSQL, & Hadoop - Bigger Is (Usually) BetterDATAVERSITY
From its widespread formal business practice to the scope of casual popular awareness, “Big Data” has a tendency to live up to its name. Featured in countless headlines, journal articles, and industry reviews, Big Data metrics and methods such as NoSQL and Hadoop have taken up plenty of the spotlight as of late. However, most of what has been written about these topics is focused on the hardware, services, and scale-out involved with them, a misguided focus that ignores the critical questions driving any shift in corporate strategy: what can Big Data do for you? Which approach to it best fits your organization? And perhaps most importantly, what is required on your end in order to spur a successful implementation process?
In the interest of answering these and other questions, this webinar will:
Provide guidance on how to think about and establish realistic Big Data management plans and expectations for generating business value, as well as on the means by which big data can complement existing data management practices
Introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL
Elaborate upon the prototyping nature of practicing Big Data techniques
Show how to demonstrate a sample use ca
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business.
Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...DATAVERSITY
Self-Service data analysis holds the promise of more rapid time-to-value for both business and IT users as advanced tooling & visualization helps make sense of raw and source data sets. Does this mean that the paradigm of ‘design-then-build’ that’s typical of data modeling is no longer relevant? Or is it more relevant than ever, as more eyes on the data means more questions about core business definitions.
Join Donna Burbank for this webinar to discuss the realities of where data modeling fits in this new paradigm.
What You Don’t Know May Hurt You – Achieving Insight and Knowledge DiscoveryConcept Searching, Inc
Think you are too busy and solutions too expensive? Take another look at how text analytics and mining can boost your bottom line, through insight and knowledge discovery. The technique is simple and the results will probably surprise you.
Stay one step ahead of the competition and find out what’s really in your content. Guest speaker Russ Stalters, information management strategist and former BP executive, explores real-life knowledge discovery scenarios, and discusses the significant return on investment achieved.
This session provides an overview of text analytics and mining, and how the appropriate solution can be used to extract and refine the dataset, by business professionals with no expertise in programming languages or databases.
The ease of use makes this concept-based searching solution ideal for organizations with analysts and knowledge workers, who need to capture live information to address issues and develop opportunities, and are not technically oriented.
Speakers:
Russ Stalters – Information Management Strategist at Clear Path Solutions
Carla Mulley – Vice President of Marketing at Concept Searching
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
In times of digitalization, every aspect of our life is connected to data. To leverage this data, companies need to understand and master analytics. In this presentation, Leo Marose will guide you through the world of big data & data science and show you his approach of how to build a data-driven organization.
Conference Overview: GARTNER SYMPOSIUM/ITXPO 2017 - Oct 1-5, Orlando, FLKelly Victor
(Just released!) Conference Overview: Explore new ways to approach critical challenges, make decisions with confidence and achieve greater impact as a leader.
Register now. Join 8,000+ Digital Leaders at the world's most important gathering of CIOs and Senior IT Executives:
GARTNER SYMPOSIUM/ITXPO 2017
1 – 5 October 2017 • Orlando, Florida
Visit the website to see digital leaders testimonials on why SYM17 is a must-attend event for their team:
http://www.gartner.com/events/na/orlando-symposium#
Learn about the emerging field of big data and advanced quantitative models and how the Rady School's MS in Business Analytics program is designed to solve important business problems.
Data-Ed Webinar: Monetizing Data Management - Show Me the MoneyDATAVERSITY
Practicality and profitability may share a page in the dictionary, but incorporating both into a data management plan can prove challenging. Many data professionals struggle to demonstrate tangible returns on data management investments, especially in industries such as healthcare where financial results aren’t necessarily an organization’s primary concern. The key to “monetizing” data management, therefore, is thinking about data in a different way: as an information solution rather than simply an IT one, using data to drive decision-making towards increased profits and potentially alternative returns on investment or value outcomes as well. Taking a broader view of data assets facilitates easier sharing of information across organizational silos, and allows for a wider understanding of the investment’s requirements and benefits.
In this webinar—designed to appeal to both business and IT attendees—your presenter will:
Describe multiple types of value produced through data-centric development and management practices
Expand on and beyond metrics meant for increasing revenues or decreasing costs—i.e. investments that directly impact an organization’s financial position
Detail how alternative statistics and valuations can be used to justify data management and quality initiatives
Data Analytics: An On-Ramp to a Better Understanding of Your BusinessSkoda Minotti
Data analytics is a hot topic in business today. But is it right for your business? What does it do for you, and most importantly, how do you get started? This executive overview explores the business implications of data analytics, while leaving the technicalities to the side.
Focus on Your Analysis, Not Your SQL CodeDATAVERSITY
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions.
Join us to learn how self-service data analytics allows analysts to:
- Utilize a drag-and-drop workflow for data and analytic processes without writing code
- Minimize data movement and ensure data integrity through in-database capabilities
- Easily work across relational and non-relational databases to deliver faster business results
Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
Advanced Analytics Governance - Effective Model Management and StewardshipDATAVERSITY
There’s been a shift toward digital business transformation with growing use of a broad spectrum of analytical capabilities (descriptive, diagnostic, predictive, prescriptive) to drive decision-making. Having a framework and overarching strategy for analytics governance is essential for data-driven organizations. Today’s advanced analytics and Business Intelligence (BI) professionals understand driving successful governance is critical for developing consistent, trusted, transparent, and effectively utilized analytics.
Join this webinar to learn best practices and vetted approaches for how to:
Ensure analytics governance is integrated with existing Data Governance processes, policies, operating model management, and Data Stewardship
Adapt governance best practices for different analytics use cases
Confirm alignment of your analytics and BI strategy with critical business objectives
Balance the rewards of digital technology and applied analytics with the compliance risks of new ethical rules, standards, and regulations
How Can You Calculate the Cost of Your Data?DATAVERSITY
Today, self-service, Cloud and big data technologies make new data preparation capabilities necessary…and possible. But, we've all been through the hype cycle and know the trough of disillusionment can come on hard and fast.
Organizations have been trying to solve the data quality problem and democratize insights for years spending millions of dollars and dedicating an increasing amount of resources to manage and govern the data. The result? Everyone is still looking to solve the problem.
Data preparation offers a new paradigm, but how can you avoid another round of minimal business impact? We’ll review a true data ROI model that helps organizations understand the value of existing versus modern data management architectures.
Implementing Big Data, NoSQL, & Hadoop - Bigger Is (Usually) BetterDATAVERSITY
From its widespread formal business practice to the scope of casual popular awareness, “Big Data” has a tendency to live up to its name. Featured in countless headlines, journal articles, and industry reviews, Big Data metrics and methods such as NoSQL and Hadoop have taken up plenty of the spotlight as of late. However, most of what has been written about these topics is focused on the hardware, services, and scale-out involved with them, a misguided focus that ignores the critical questions driving any shift in corporate strategy: what can Big Data do for you? Which approach to it best fits your organization? And perhaps most importantly, what is required on your end in order to spur a successful implementation process?
In the interest of answering these and other questions, this webinar will:
Provide guidance on how to think about and establish realistic Big Data management plans and expectations for generating business value, as well as on the means by which big data can complement existing data management practices
Introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL
Elaborate upon the prototyping nature of practicing Big Data techniques
Show how to demonstrate a sample use ca
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business.
Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...DATAVERSITY
Self-Service data analysis holds the promise of more rapid time-to-value for both business and IT users as advanced tooling & visualization helps make sense of raw and source data sets. Does this mean that the paradigm of ‘design-then-build’ that’s typical of data modeling is no longer relevant? Or is it more relevant than ever, as more eyes on the data means more questions about core business definitions.
Join Donna Burbank for this webinar to discuss the realities of where data modeling fits in this new paradigm.
What You Don’t Know May Hurt You – Achieving Insight and Knowledge DiscoveryConcept Searching, Inc
Think you are too busy and solutions too expensive? Take another look at how text analytics and mining can boost your bottom line, through insight and knowledge discovery. The technique is simple and the results will probably surprise you.
Stay one step ahead of the competition and find out what’s really in your content. Guest speaker Russ Stalters, information management strategist and former BP executive, explores real-life knowledge discovery scenarios, and discusses the significant return on investment achieved.
This session provides an overview of text analytics and mining, and how the appropriate solution can be used to extract and refine the dataset, by business professionals with no expertise in programming languages or databases.
The ease of use makes this concept-based searching solution ideal for organizations with analysts and knowledge workers, who need to capture live information to address issues and develop opportunities, and are not technically oriented.
Speakers:
Russ Stalters – Information Management Strategist at Clear Path Solutions
Carla Mulley – Vice President of Marketing at Concept Searching
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
In times of digitalization, every aspect of our life is connected to data. To leverage this data, companies need to understand and master analytics. In this presentation, Leo Marose will guide you through the world of big data & data science and show you his approach of how to build a data-driven organization.
Conference Overview: GARTNER SYMPOSIUM/ITXPO 2017 - Oct 1-5, Orlando, FLKelly Victor
(Just released!) Conference Overview: Explore new ways to approach critical challenges, make decisions with confidence and achieve greater impact as a leader.
Register now. Join 8,000+ Digital Leaders at the world's most important gathering of CIOs and Senior IT Executives:
GARTNER SYMPOSIUM/ITXPO 2017
1 – 5 October 2017 • Orlando, Florida
Visit the website to see digital leaders testimonials on why SYM17 is a must-attend event for their team:
http://www.gartner.com/events/na/orlando-symposium#
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from ForresterCubic Corporation
Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions.
To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter.
This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to:
- Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt
- Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments
- Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs
- Enable real-time analytics with existing business intelligence and data assets.
Large language models in higher educationPeter Trkman
Discussing the possibilities of large language models for the automatic generation of academic content by the students (e.g. master thesis), and the related need for changes in the way in which to educate and evaluate students.
Once you’ve made the decision to leverage AI and/or machine learning, now you need to figure out how you will source the training data that is necessary for a fully functioning algorithm. Depending on your use case, you might need a significant amount of training data, and you’ll want to consider how that is labeled and annotated too.
View Applause's webinar with Cognilytica principal analysts Ronald Schmelzer and Kathleen Walch, alongside Kristin Simonini, Applause’s Vice President of Product, as they tackle the modern challenges that today’s companies face with sourcing training data.
The Evolution Of Competitive Intelligence Dec09 Finalrotciv
This presentation was part of the conference agenda for London Online in December 2009. It provides a high level overview of the way competitive intelligence analysts have benefitted from the evolving Web. It also provides a brief view of the next area of development, Semantic Search
Empowering your Enterprise with a Self-Service Data Marketplace (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uqcAN0
Self-service is a major goal of modern data strategists. A successfully implemented self-service initiative means that business users have access to holistic and consistent views of data regardless of its location, source or type. As data unification and data collaboration become key critical success factors for organizations, data catalogs play a key role as the perfect companion for a virtual layer to fully empower those self-service initiatives and build a self-service data marketplace requiring minimal IT intervention.
Denodo’s Data Catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It provides business users with the tool to generate their own insights with proper security, governance, and guardrails.
In this session we will cover:
- The role of a virtual semantic layer in self-service initiatives
- Key ingredients of a successful self-service data marketplace Self-service (consumption) vs. inventory catalogs
- Best practices and advanced tips for successful deployment
- A Demonstration: Product Demo
- Examples of customers using Denodo’s Data Catalog to enable self-service initiatives
Presentation to Analytics Network of the OR Society Nov 2020Paul Laughlin
Presentation on 'The Softer Skills that Analysts need' presented by Paul Laughlin at a virtual event run for the Analytics Network group within the UK OR Society. Exploring Paul's 9 Step Model for effective analysis & explaining how Softer Skills are essential throughout that workflow.
Revolutionizing the Legal Industry with Spark, NLP and Azure Databricks at Cl...Databricks
From zero to data science in a legal firm: how one of the world’s largest law firms is reshaping operations with advanced analytics. Clifford Chance LLP is one of the ten largest law firms in the world. With thousands of global clients their teams handle millions of legal documents every year.
The data science team will share their approach to building an agile data science lab from zero on top of Apache Spark, Azure Databricks and MLflow. They will deep dive into how they used deep learning for natural language processing in the classification of large documents using MLflow and Hyperopt for model comparison and hyperparameter optimization.
Enterprise Data Marketplace: A Centralized Portal for All Your Data AssetsDenodo
Watch full webinar here: https://bit.ly/3OLv0jY
Organizations continue to collect mounds of data and it is spread over different locations and in different formats. The challenge is navigating the vastness and complexity of the modern data ecosystem to find the right data to suit your specific business purpose. Data is an important corporate asset and it needs to be leveraged but also protected.
By adopting an alternate approach to data management and adapting a logical data architecture, data can be democratized while providing centralized control within a distributed data landscape. The web-based Data Catalog tool a single access point for secure enterprise-wide data access and governance. This corporate data marketplace provides visibility into your data ecosystem and allows data to be shared without compromising data security policies.
Catch this on-demand session to understand how this approach can transform how you leverage data across the business:
- Empower the knowledge worker with data and increase productivity
- Promote data accuracy and trust to encourage re-use of important data assets
- Apply consistent security and governance policies across the enterprise data landscape
Similar to Gain Competitive Advantage by Increasing Knowledge Productivity (20)
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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.
3. CID GmbH
• Digitization of Business Processes
since 1997
• Software Development based on
Microsoft .net
Pattern Science AG
• Research & Development on
Text Mining, Semantics &
Machine Learning since 2007
• Scientific Cooperations
CID Consulting GmbH
• Technology-focused Consulting
since 2008
• Implementation of
Knowledge Management and
Competitive Intelligence Processes
Hasselroth, Germany
• 150 Employees
• Founded 1997
Enterprise-ready
Software Solutions for
Efficient Processes
combined with
Innovative Research
and Development
Delivering Smart Answers
4. • Which challenges meet companies today?
• Which solution components are available?
• What can IT contribute to Knowledge Productivity?
Focus: Knowledge Productivity
Which challenges meet Information Workers
during their daily work?
How can they improve Knowledge
Productivity effectively?
6. Competitive Intelligence
Use CasesSources
over 11.000 Websites
(competitors, news,
industry magazines,
scientific publications,
…)
over a Million of
Market Data
(financials, sales,
advertisement spending,
…)
Users
Professional Analysts
Management
End-Users
company-wide
Any new product
launches?
What are new
trends in my
market?
How do legislation
and regulation
change?
How do I get
in-depth
information
easily?
7. Technology Management
Sources
over 10.000 Websites
(competitors, news,
industry magazines,
scientific publications,
other industries
…)
Patents from
Selected Groups
European Patent Office
Use Cases Users
Professional Analysts
What are new
trends in my
market?
What are relevant
trends in other
industries?
Does a competitor
move into a new
segment?
How do research,
development &
marketing relate?
8. Product Development
Sources
Thousands
of Service Tickets
collected within the
Service Portal
Use Cases Users
Professional Analysts
Management
Are there any
trends in product-
related issues?
How to improve a
product’s quality
and lifecycle?
How to improve
SLAs with
customers?
How to
consolidate
service
information?
9. Market Monitoring
Sources
over 300 Websites
(competitors, news,
industry magazines,
scientific publications,
other industries
…)
Use Cases Users
Professional Analysts
Management
End-Users
company-wide
Any new product
launches?
What are new
trends in my
market?
Does a competitor
move into a new
segment?
How do I get
in-depth
information
easily?
10. many sources
various formats
little structure
search quickly
analyze aspects
understand quickly
identify correlations
detect trends
provide individual insights
search comprehensively
examine holistically
reduce dependencies
Challenges
Starting Point
Objective
11. Level of Implementation
LevelofEfficiency
++
++
many sources
various formats
little structure
search quickly
analyze aspects
understand quickly
identify correlations
detect trends
provide individual
insights
search comprehensively
examine holistically
reduce dependencies
12. Level of Implementation
LevelofEfficiency
++
++
external
Information Collection internal
many sources
various formats
little structure
search quickly
analyze aspects
understand quickly
identify correlations
detect trends
provide individual
insights
search comprehensively
examine holistically
reduce dependencies
14. Information Demand
• websites
• press releases
• sales reports
• Social Media
for operational & strategic
decisions
• websites
• press releases
• signed contracts
• CRM
• service & support
• Social Media
• universities
• research institutes
• publications
• conferences
• patents
• studies
• new law
• standards
• decisions
• admissions
Competition
Authorities &
Legislation
• news about...
• industry
• market players
• incidents, e.g. accidents
Press & Media
Customers
Research &
Development
• innovation
• influencing factors on
product and industry
other industries
16. Crawler
Wolfsburg (Germany), 08.11.2006 -
"The Presidium of the Supervisory
Board of Volkswagen AG and Chairman
of the Board, Dr. Bernd Pischetsrieder,
have agreed by consensus he retires on
31.12.2006."
This short note was published by the
VW Group last night about the
resigning of its chief executive.
Successor will be the CEO of Audi,
Martin Winterkorn. There were no
further explanations by the company.
Also the largest shareholder of VW, the
sports car manufacturer Porsche AG,
did not want to comment.
Crawling of relevant parts of
web sites
Crawler
Centralized
Index
Internal Systems (SharePoint, CRM, DMS...)
Interfaces
Solution
17. Level of Implementation
LevelofEfficiency
++
++
external
Information Collection internal
many sources
various formats
little structure
search quickly
analyze aspects
understand quickly
identify correlations
detect trends
provide individual
insights
search comprehensively
examine holistically
reduce dependencies
18. Level of Implementation
LevelofEfficiency
++
++
Information Collection internal
external
Search
many sources
various formats
little structure
search quickly
analyze aspects
understand quickly
identify correlations
detect trends
provide individual
insights
search comprehensively
examine holistically
reduce dependencies
48. ++
++0
centralized indexing of
internal information
Systematic collection of
external information
Enterprise Search
Intelligent Search
with related terms and
ontological concepts
Consolidated Search
in external & internal
information
Contextualization
Pre-Analysis
for efficient
interpretation
Exploratory
Search
Self-Service
Dashboards
Automated Detection of
Topics and Trends
Intranet Portals
Solution
Visualization Information
Sharing
Objective
Level of Implementation
LevelofEfficiency
49. Objective
Mission accomplished
Alexander Stumpfegger
CID Consulting GmbH
Managing Director
Gewerbepark Birkenhain 1
D-63579 Freigericht
phone +49 6051 8846-0
direct d. +49 6051 8846-101
e-mail a.stumpfegger@cid.de
web cid.com