Discover the business value of Open Data by Majken SanderMajken Sander
Majken explains how to create a hub and start exploiting open data. Majken discusses which data can be found from external sources and how open data can add value by enhancing existing company data to gain new insights. There is a dataset out there for your business to become even more data driven. Join Majken to find it
Big data -_14._maerz_mitarbeiterforschung_kundenevent_v2.pptx__schreibgeschue...Aravindharamanan S
This document summarizes GfK's expertise with big data and examples of big data projects. It discusses how GfK turns big data into smart data through proprietary algorithms, industry expertise, and a reference layer. An example project is the Data Lab Market Forecaster, which integrates data from GfK consumer and crossmedia panels, including purchase behavior, media usage, and location data. The document also briefly mentions an example social media project presented in November 2015.
Design Thinking for Data Superwomen & SupermenDatentreiber
Martin Szugat from Datentreiber held a keynote at the Predictive Analytics World Business Conference on November 14th, 2018 to share his knowledge on how to transform a business with an individual and successful data strategy for interdisciplinary teams.
Talk at IEEE Big Data/Cloud conference in Santa Clara, June 28th, 2013.Jari Koister
This document provides 4 pieces of advice for big data initiatives:
1. Don't get bogged down in technology and focus on business goals.
2. Find a data quality and enrichment provider to help with complex data challenges.
3. Be realistic about what can be achieved given investment and data constraints.
4. Scale is expensive, so sample data when possible to reduce costs and complexity.
The document discusses the changing role of data and analytics in business. It notes that while tools like Hadoop excel at processing large amounts of data, they are slow for interactive business intelligence queries. Modern data platforms utilize in-memory analytics for low-latency querying and more advanced techniques like machine learning. The goal is to move successful analytic projects from a data science lab into regular business operations.
致詞歡迎:Big Data 無所不在,Data Technology 無 C 不歡Etu Solution
This document contains the opening remarks from Lin Longfen, the general manager of Jingcheng Group. It discusses how Gartner dropped "Big Data" from its hype cycle of emerging technologies in 2015 because it is now considered a mainstream part of many industries. Big data is still essential for major trends like the Internet of Things, Industry 4.0, and smart everything. The document emphasizes that understanding customers ("C") is key to a company's ("B") competitive advantage in the digital economy, and that leveraging industry data is a common development strategy across Jingcheng Group's business units.
Martin Szugat gave a guest lecture on developing a data strategy. He explained that a data strategy guides how a business uses data and analytics to make decisions and gain value. It involves understanding user and business needs, exploring available data sources, and developing analytics use cases and a roadmap to increase the maturity of data-driven processes, products, and business models over time. Szugat also discussed common reasons why many data projects and products fail, and emphasized the importance of designing data strategies using proven approaches like CRISP-DM to ensure business impact, user acceptance, and feasibility based on available data.
How Big Data technology affects businesses?NexSoftsys
Top 5 big data technology for a modern business to manage supply chains, quickly understand the business customer’s requirements and identify the fake transaction.
Discover the business value of Open Data by Majken SanderMajken Sander
Majken explains how to create a hub and start exploiting open data. Majken discusses which data can be found from external sources and how open data can add value by enhancing existing company data to gain new insights. There is a dataset out there for your business to become even more data driven. Join Majken to find it
Big data -_14._maerz_mitarbeiterforschung_kundenevent_v2.pptx__schreibgeschue...Aravindharamanan S
This document summarizes GfK's expertise with big data and examples of big data projects. It discusses how GfK turns big data into smart data through proprietary algorithms, industry expertise, and a reference layer. An example project is the Data Lab Market Forecaster, which integrates data from GfK consumer and crossmedia panels, including purchase behavior, media usage, and location data. The document also briefly mentions an example social media project presented in November 2015.
Design Thinking for Data Superwomen & SupermenDatentreiber
Martin Szugat from Datentreiber held a keynote at the Predictive Analytics World Business Conference on November 14th, 2018 to share his knowledge on how to transform a business with an individual and successful data strategy for interdisciplinary teams.
Talk at IEEE Big Data/Cloud conference in Santa Clara, June 28th, 2013.Jari Koister
This document provides 4 pieces of advice for big data initiatives:
1. Don't get bogged down in technology and focus on business goals.
2. Find a data quality and enrichment provider to help with complex data challenges.
3. Be realistic about what can be achieved given investment and data constraints.
4. Scale is expensive, so sample data when possible to reduce costs and complexity.
The document discusses the changing role of data and analytics in business. It notes that while tools like Hadoop excel at processing large amounts of data, they are slow for interactive business intelligence queries. Modern data platforms utilize in-memory analytics for low-latency querying and more advanced techniques like machine learning. The goal is to move successful analytic projects from a data science lab into regular business operations.
致詞歡迎:Big Data 無所不在,Data Technology 無 C 不歡Etu Solution
This document contains the opening remarks from Lin Longfen, the general manager of Jingcheng Group. It discusses how Gartner dropped "Big Data" from its hype cycle of emerging technologies in 2015 because it is now considered a mainstream part of many industries. Big data is still essential for major trends like the Internet of Things, Industry 4.0, and smart everything. The document emphasizes that understanding customers ("C") is key to a company's ("B") competitive advantage in the digital economy, and that leveraging industry data is a common development strategy across Jingcheng Group's business units.
Martin Szugat gave a guest lecture on developing a data strategy. He explained that a data strategy guides how a business uses data and analytics to make decisions and gain value. It involves understanding user and business needs, exploring available data sources, and developing analytics use cases and a roadmap to increase the maturity of data-driven processes, products, and business models over time. Szugat also discussed common reasons why many data projects and products fail, and emphasized the importance of designing data strategies using proven approaches like CRISP-DM to ensure business impact, user acceptance, and feasibility based on available data.
How Big Data technology affects businesses?NexSoftsys
Top 5 big data technology for a modern business to manage supply chains, quickly understand the business customer’s requirements and identify the fake transaction.
Neo4j Graph Data Platform: Making Your Data More IntelligentNeo4j
This document discusses the Neo4j graph data platform and how it can help organizations make their data more intelligent. Some key points:
- By 2025, 175 zettabytes of data will be generated annually, but over half remains unquantified and untapped due to a lack of connections between data.
- Neo4j can unlock these connections through its graph database approach, which is designed for connected data. This allows for accelerated innovation through AI/ML and real-time connected insights.
- Graph databases like Neo4j provide significant performance advantages over relational and NoSQL databases for queries involving connections in data, enabling "minutes to milliseconds" response times even at large scale
You Have the Data, Now What? (Chris Lynch) - 2014 Boston Data Festival -freshdatabos
This document provides information about the 2014 Boston Data Festival hosted by Chris Lynch and Atlas Venture. It discusses the growth of the big data market and challenges of big data analytics. It also lists Atlas Venture's investments in several big data startups and describes Hack/Reduce, a Boston-based community space that provides resources for working with big data. The final pages promote a charity event on December 8th to help fight childhood cancer.
Collaborative Data UX Design - Virtually and Phyically Datentreiber
Many data products fail, partly because users do not understand or accept the software. To avoid this, analytics solutions e.g. KPI dashboards should be designed together with the users and this is especially true for the user interface.
At the Data Brain Meetup Datentreiber Martin Szugat showed three wireframing tools to sketch UI designs collaboratively with the users:
1) the virtual collaboration tool Miro,
2) the PowerPoint add-on PowerMockup and
3) the physical Dashboard Wireframing Kit.
SnapLogic At Tableau Conference - Sept 2013 #tcc13Maneesh Joshi
This document discusses SnapLogic, an integration platform that allows non-technical users to access and analyze data from various sources. It provides three customer examples that have used SnapLogic to improve marketing analytics. A retail company used SnapLogic to empower marketing teams to access metrics from sources like Google and Facebook. A consumer goods company deployed SnapLogic to pull social media and analytics data for reporting. SnapLogic offers benefits like faster access to more data sources, lower costs, and empowering non-technical users.
New ThingWorx Analytics Builder Enhances PTC’s Internet of Things PlatformPTC
New IoT Analytics Tool Provides Simple Interface to Create and Manage Advanced Analytics within ThingWorx-powered Solutions
NEEDHAM, Mass. – October 6, 2016 –– PTC (NASDAQ: PTC) today announced the availability of ThingWorx® Analytics Builder, the latest component of its ThingWorx® Internet of Things (IoT) platform. ThingWorx Analytics Builder is an interactive user interface for creating and managing advanced analytic models for use in ThingWorx-powered solutions. With the addition of ThingWorx Analytics Builder, PTC further enhances its leading IoT analytics capabilities through the ThingWorx platform.
The document discusses how lessons learned from analyzing threats on the battlefield after 9/11 can be applied to analyzing financial risks. It advocates using multi-nodal network analysis and data analytics to identify hidden relationships and risks across large, complex global financial networks, as is done to identify terrorist networks. This approach provides a holistic view of risk exposure and can help mitigate issues like fraud, money laundering, and reputational risks through more efficient identification of linkages. The document argues that if analytics are correctly applied, they can transform the financial industry's ability to manage risk.
Read the full post at https://www.fourquadrant.com/gartner-go-to-market-strategy/
Gartner's IT Predictions
Key technology drivers that will impact go to market strategy and tactics include: intelligent things, collecting massive amounts of data, artificial intelligence and machine learning.
Gartner identifies 3 key themes that form the basis for the Top 10 strategic technology trends:
- Intelligent
- Digital
- and Mesh
The technologies noted above are at the front-end of the technology adoption curve but are expected to break out of an emerging state and stand to have substantial disruptive potential across industries.
Read Pragmatic Posts on B2B Marketing - https://www.fourquadrant.com/marketing-resource-blog/
Download Go to Market Templates (FREE) - https://www.fourquadrant.com/marketing-tempates/
View the Go to Market PowerPoint Slide Library - https://www.fourquadrant.com/marketing-slides/
Leverage Proven Go to Market Planning Templates - https://www.fourquadrant.com/products/
This document lists upcoming data analytics events and webinars, including a webinar on getting started with people analytics on September 9, 2020. It also provides links to live COVID-19 data portals and recommends reports on business intelligence, analytics platforms, master data management solutions, and data integration tools. It includes contact information for two individuals, Phillip Simulis and Hector Del Castillo.
Top 15 Predictions about Data Analytics and AI for Decision MakersCygnet Infotech
Data Analytics and Artificial Intelligence are transforming businesses and societies in general. Know about how valuable they are for CXOs and other Decision Makers.
This document discusses data science, including its hype and realities. It provides an overview of data science concepts like big data, data warehousing, business intelligence, and predictive analytics. It also discusses the data science process and pipeline. Examples of data science use cases in oil and gas are given. The document provides advice on how to get started in data science, including training, experience, tools, and passion. Finally, potential topics for future data science meetups are listed.
Mark van Rijmenam, global big data influencer and keynote speaker, gave the opening keynote for Seamless Dubai 2016. His keynote provided insights how organisations can win customers for life with predictive analytics.
This document discusses how big data and data science are transforming marketing. It defines big data as methods and technologies for integrating, storing, and analyzing poly-structured data at large scale. It notes that big data solutions address gaps in the market and enable next-generation retailers to track individual customer behavior in real time. The document promotes an upcoming seminar on data science and the growing demand for data scientists.
Which technology trends will create the Year of Transition? Here are the top 7 technology trends for 2018 that will affect organisations and governments.
RightScale Roadtrip - The Power of a Cloud-Enabled AgencyRightScale
This document summarizes a presentation about using RightScale technology for digital marketing campaigns. It discusses how RightScale allows for on-demand scalability to handle unpredictable traffic, quick provisioning to meet tight deadlines, and resilient architectures to reduce the risk of outages disrupting campaigns. Examples are given of companies using RightScale to scale a chocolate promotion and launch a virtual world in time for a catalog drop despite tight deadlines. RightScale is said to provide auto-scaling, cost optimization, monitoring and multi-region capabilities to help companies meet service level agreements and limit downtime.
Un caso di studio sui big data - Campus Connestions Summit 2018 - #CCS18Angelo Gino Varrati
In this talk I talk about Big Data (introduction to), Microsoft Azure and its services for the Big Data. I expose and experiment of sentiment analysis on Twitter using Azure Machine Learning .
"Agile Analytics" - Marianne Faro, Analytics Competence Lead at ItilityDataconomy Media
This document summarizes a Big Data meetup in Amsterdam on Agile Analytics. It discusses the 3 V's of big data - volume, velocity, and variety. It also discusses the 3 V's of an analytics team - different types of customers/projects, speed of starting up projects using Agile methods, and roles on the team. The document advocates taking an "elephant approach" to Agile Analytics, meaning biting off pieces of big projects bit by bit. It also describes Itility as a company that designs and manages end-to-end digital solutions and offers a managed analytics platform as a cloud-like service to customers.
How to Transform IT Operations with Machine Learning - Apply ContextDevOps.com
IT operations is complex. And it generates a ton of data. So much data, that it can quickly overwhelm your IT Operations team’s ability to process it. Is more data really better? Or is it noise that inhibits action? While Machine Learning promises to make sense of it all, it requires complete, accurate, and unfragmented data. Otherwise, the old adage “Garbage in, Garbage out” prevails.
This document discusses emerging technology trends in social analytics and predictive analysis. It provides examples of how companies like Ford, IBM, and SportingIndex are using predictive technology and big data analytics in sports to analyze historical data and predict outcomes. Social media analytics tools like ThisMoment and Sprout Social are also discussed that help analyze social marketing efforts and monitor social media conversations. The document emphasizes the importance of data visualization and interactive data formats to effectively communicate insights from large and complex data sets.
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
Exciting it trends in 2015 why you should consider shifting and upgrading yo...lithanhall
This document discusses exciting IT trends for 2015 and high demand IT career paths. It summarizes Gartner's top 10 strategic technology trends for 2015, including computing everywhere, the internet of things, 3D printing, advanced analytics, context-rich systems, smart machines, cloud/client computing, software-defined applications and infrastructure, web-scale IT, and risk-based security. It also outlines 5 in-demand IT career tracks: enterprise resource planning, systems management, business intelligence/big data analytics, technology sales and marketing, and technopreneurship. Finally, it introduces Lithan Hall Academy which provides skills training programs to help workers transition into these high-demand IT roles.
Neo4j Graph Data Platform: Making Your Data More IntelligentNeo4j
This document discusses the Neo4j graph data platform and how it can help organizations make their data more intelligent. Some key points:
- By 2025, 175 zettabytes of data will be generated annually, but over half remains unquantified and untapped due to a lack of connections between data.
- Neo4j can unlock these connections through its graph database approach, which is designed for connected data. This allows for accelerated innovation through AI/ML and real-time connected insights.
- Graph databases like Neo4j provide significant performance advantages over relational and NoSQL databases for queries involving connections in data, enabling "minutes to milliseconds" response times even at large scale
You Have the Data, Now What? (Chris Lynch) - 2014 Boston Data Festival -freshdatabos
This document provides information about the 2014 Boston Data Festival hosted by Chris Lynch and Atlas Venture. It discusses the growth of the big data market and challenges of big data analytics. It also lists Atlas Venture's investments in several big data startups and describes Hack/Reduce, a Boston-based community space that provides resources for working with big data. The final pages promote a charity event on December 8th to help fight childhood cancer.
Collaborative Data UX Design - Virtually and Phyically Datentreiber
Many data products fail, partly because users do not understand or accept the software. To avoid this, analytics solutions e.g. KPI dashboards should be designed together with the users and this is especially true for the user interface.
At the Data Brain Meetup Datentreiber Martin Szugat showed three wireframing tools to sketch UI designs collaboratively with the users:
1) the virtual collaboration tool Miro,
2) the PowerPoint add-on PowerMockup and
3) the physical Dashboard Wireframing Kit.
SnapLogic At Tableau Conference - Sept 2013 #tcc13Maneesh Joshi
This document discusses SnapLogic, an integration platform that allows non-technical users to access and analyze data from various sources. It provides three customer examples that have used SnapLogic to improve marketing analytics. A retail company used SnapLogic to empower marketing teams to access metrics from sources like Google and Facebook. A consumer goods company deployed SnapLogic to pull social media and analytics data for reporting. SnapLogic offers benefits like faster access to more data sources, lower costs, and empowering non-technical users.
New ThingWorx Analytics Builder Enhances PTC’s Internet of Things PlatformPTC
New IoT Analytics Tool Provides Simple Interface to Create and Manage Advanced Analytics within ThingWorx-powered Solutions
NEEDHAM, Mass. – October 6, 2016 –– PTC (NASDAQ: PTC) today announced the availability of ThingWorx® Analytics Builder, the latest component of its ThingWorx® Internet of Things (IoT) platform. ThingWorx Analytics Builder is an interactive user interface for creating and managing advanced analytic models for use in ThingWorx-powered solutions. With the addition of ThingWorx Analytics Builder, PTC further enhances its leading IoT analytics capabilities through the ThingWorx platform.
The document discusses how lessons learned from analyzing threats on the battlefield after 9/11 can be applied to analyzing financial risks. It advocates using multi-nodal network analysis and data analytics to identify hidden relationships and risks across large, complex global financial networks, as is done to identify terrorist networks. This approach provides a holistic view of risk exposure and can help mitigate issues like fraud, money laundering, and reputational risks through more efficient identification of linkages. The document argues that if analytics are correctly applied, they can transform the financial industry's ability to manage risk.
Read the full post at https://www.fourquadrant.com/gartner-go-to-market-strategy/
Gartner's IT Predictions
Key technology drivers that will impact go to market strategy and tactics include: intelligent things, collecting massive amounts of data, artificial intelligence and machine learning.
Gartner identifies 3 key themes that form the basis for the Top 10 strategic technology trends:
- Intelligent
- Digital
- and Mesh
The technologies noted above are at the front-end of the technology adoption curve but are expected to break out of an emerging state and stand to have substantial disruptive potential across industries.
Read Pragmatic Posts on B2B Marketing - https://www.fourquadrant.com/marketing-resource-blog/
Download Go to Market Templates (FREE) - https://www.fourquadrant.com/marketing-tempates/
View the Go to Market PowerPoint Slide Library - https://www.fourquadrant.com/marketing-slides/
Leverage Proven Go to Market Planning Templates - https://www.fourquadrant.com/products/
This document lists upcoming data analytics events and webinars, including a webinar on getting started with people analytics on September 9, 2020. It also provides links to live COVID-19 data portals and recommends reports on business intelligence, analytics platforms, master data management solutions, and data integration tools. It includes contact information for two individuals, Phillip Simulis and Hector Del Castillo.
Top 15 Predictions about Data Analytics and AI for Decision MakersCygnet Infotech
Data Analytics and Artificial Intelligence are transforming businesses and societies in general. Know about how valuable they are for CXOs and other Decision Makers.
This document discusses data science, including its hype and realities. It provides an overview of data science concepts like big data, data warehousing, business intelligence, and predictive analytics. It also discusses the data science process and pipeline. Examples of data science use cases in oil and gas are given. The document provides advice on how to get started in data science, including training, experience, tools, and passion. Finally, potential topics for future data science meetups are listed.
Mark van Rijmenam, global big data influencer and keynote speaker, gave the opening keynote for Seamless Dubai 2016. His keynote provided insights how organisations can win customers for life with predictive analytics.
This document discusses how big data and data science are transforming marketing. It defines big data as methods and technologies for integrating, storing, and analyzing poly-structured data at large scale. It notes that big data solutions address gaps in the market and enable next-generation retailers to track individual customer behavior in real time. The document promotes an upcoming seminar on data science and the growing demand for data scientists.
Which technology trends will create the Year of Transition? Here are the top 7 technology trends for 2018 that will affect organisations and governments.
RightScale Roadtrip - The Power of a Cloud-Enabled AgencyRightScale
This document summarizes a presentation about using RightScale technology for digital marketing campaigns. It discusses how RightScale allows for on-demand scalability to handle unpredictable traffic, quick provisioning to meet tight deadlines, and resilient architectures to reduce the risk of outages disrupting campaigns. Examples are given of companies using RightScale to scale a chocolate promotion and launch a virtual world in time for a catalog drop despite tight deadlines. RightScale is said to provide auto-scaling, cost optimization, monitoring and multi-region capabilities to help companies meet service level agreements and limit downtime.
Un caso di studio sui big data - Campus Connestions Summit 2018 - #CCS18Angelo Gino Varrati
In this talk I talk about Big Data (introduction to), Microsoft Azure and its services for the Big Data. I expose and experiment of sentiment analysis on Twitter using Azure Machine Learning .
"Agile Analytics" - Marianne Faro, Analytics Competence Lead at ItilityDataconomy Media
This document summarizes a Big Data meetup in Amsterdam on Agile Analytics. It discusses the 3 V's of big data - volume, velocity, and variety. It also discusses the 3 V's of an analytics team - different types of customers/projects, speed of starting up projects using Agile methods, and roles on the team. The document advocates taking an "elephant approach" to Agile Analytics, meaning biting off pieces of big projects bit by bit. It also describes Itility as a company that designs and manages end-to-end digital solutions and offers a managed analytics platform as a cloud-like service to customers.
How to Transform IT Operations with Machine Learning - Apply ContextDevOps.com
IT operations is complex. And it generates a ton of data. So much data, that it can quickly overwhelm your IT Operations team’s ability to process it. Is more data really better? Or is it noise that inhibits action? While Machine Learning promises to make sense of it all, it requires complete, accurate, and unfragmented data. Otherwise, the old adage “Garbage in, Garbage out” prevails.
This document discusses emerging technology trends in social analytics and predictive analysis. It provides examples of how companies like Ford, IBM, and SportingIndex are using predictive technology and big data analytics in sports to analyze historical data and predict outcomes. Social media analytics tools like ThisMoment and Sprout Social are also discussed that help analyze social marketing efforts and monitor social media conversations. The document emphasizes the importance of data visualization and interactive data formats to effectively communicate insights from large and complex data sets.
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
Exciting it trends in 2015 why you should consider shifting and upgrading yo...lithanhall
This document discusses exciting IT trends for 2015 and high demand IT career paths. It summarizes Gartner's top 10 strategic technology trends for 2015, including computing everywhere, the internet of things, 3D printing, advanced analytics, context-rich systems, smart machines, cloud/client computing, software-defined applications and infrastructure, web-scale IT, and risk-based security. It also outlines 5 in-demand IT career tracks: enterprise resource planning, systems management, business intelligence/big data analytics, technology sales and marketing, and technopreneurship. Finally, it introduces Lithan Hall Academy which provides skills training programs to help workers transition into these high-demand IT roles.
Apache spark empowering the real time data driven enterprise - StreamAnalytix...Impetus Technologies
Apache Spark is one of the most popular Big Data frameworks today. It is fast becoming the de facto technology choice for stream processing, real-time analytics, data science and machine learning applications at scale. It has moved well beyond the early-adopter phase, is supported by a vibrant open source community and is enjoying accelerated adoption in enterprises.
Join our guest speaker from Forrester Research, VP & Principal Analyst, Mike Gualtieri and StreamAnalytix, Product Head, Anand Venugopal for a discussion on the trends and directions defining the growing importance of Apache Spark for stream processing, machine learning and other advanced data analytics applications.
The document discusses how modern software architectures can help tame big data. It introduces the speakers and provides an overview of WidasConcepts. The agenda includes a discussion of how big data can help businesses, an example of big data applied in the CarbookPlus platform, and new software architectures for big data. Real-time systems and architectures like lambda architecture are presented as ways to process big data at high velocity and volume. The conclusion emphasizes that big data improves business efficiency but requires tailored implementations and new skills.
This document discusses Hadoop and big data. It notes that digital data doubles every two years and that 85% of data is unstructured. Hadoop provides a cheaper way to store large amounts of both structured and unstructured data compared to traditional storage options. Hadoop also allows data to be stored first before defining what questions will be asked of the data.
How Data-Driven Approaches are Changing Your Data Management Strategies
Introducing data-driven strategies into your business model alters the way your organization manages and provides information to your customers, partners and employees. Gone are the days of “waterfall” implementation strategies from relational data to applications within a data center. Now, data-driven business models require agile implementation of applications based on information from all across an organization–on-premises, cloud, and mobile–and includes information from outside corporate walls from partners, third-party vendors, and customers. Data management strategies need to be ready to meet these challenges or your new and disruptive business models will fail at the most critical time: when your customers want to access it.
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
The document discusses how operators should view and utilize big data. It provides perspectives from industry experts on how big data analytics can provide value if aligned with business strategy, how different tools may be useful for different business functions, and how big data can integrate with existing analytics environments. The experts discuss starting with pilots and focusing on clear goals, selecting tools based on needs, and emphasizing interpretation of results over just collecting more data.
The world around us is changing. Data is embedded in everything, and users from all lines of business want to leverage this data to influence decisions. The trick is to create a culture for pervasive analytics and empower the business to use data everywhere.
The core enabling technology to make this happen is Apache Hadoop. By leveraging Hadoop, organizations of all sizes and across all industries are making business models more predictable, and creating significant competitive advantages using big data.
Join Cloudera and Forrester to learn:
- What we mean by pervasive analytics, how it impacts your organization, and how to get started
- How leading organizations are using pervasive analytics for competitive advantage
- How Cloudera’s extensive partner ecosystem complements your strategy, helping deliver results faster
1) In-memory computing is growing rapidly, with the total data market expected to grow from $69 billion in 2015 to $132 billion in 2020.
2) In-memory databases are gaining popularity for applications that require fast response times, like telecommunications and mobile advertising, as memory access is faster than disk access.
3) Modern applications are driving adoption of in-memory solutions as they generate more data from more users and transactions and require faster performance to handle growing traffic.
4) Two examples presented were DellEMC using MemSQL for a real-time customer 360 application and an IoT logistics application called MemEx that processes sensor data from warehouses for predictive analytics.
SAP Forum Ankara 2017 - "Verinin Merkezine Seyahat"MDS ap
The document discusses digital transformation and the journey to data-driven insights. It provides an overview of data types and how data has grown exponentially over time. Both structured and unstructured data are discussed, with examples of semi-structured data like emails and reports. The value of understanding all data sources is emphasized for gaining competitive advantages through analytics. New technologies like complex event processing are enabling lightning-fast action based on diverse data. Finally, the presentation introduces SAP HANA Vora for bridging the divide between enterprise and big data systems to facilitate precision decision making.
This document discusses strategies for telcos to leverage big data. It begins by outlining the shift from traditional "small data" paradigms to new "big data" approaches characterized by processing vast amounts of data from both internal and external sources. It then provides examples of the types of internal and external data available to telcos and how this data could be used. The document also outlines some of the main challenges telcos may face in developing big data capabilities, such as competition from internet companies and ensuring privacy and regulatory compliance. It concludes by emphasizing the importance of a gradual, pilot-based approach to building big data strategies.
Modern Data Challenges require Modern Graph TechnologyNeo4j
This session focuses on key data trends and challenges impacting enterprises. And, how graph technology is evolving to future-proof data strategy and architectures.
The 4 Biggest Trends In Big Data and Analytics Right For 2021Bernard Marr
Big Data is a term that’s come to be used to describe the technology and practice of working with data that’s not only large in volume but also fast and comes in many different forms. For every Elon Musk with a self-driving car to sell, or Jeff Bezos with a cashier-less convenience store, there is a sophisticated Big Data operation and an army of clever data scientists who’ve turned a vision into reality.
This document discusses future trends in big data. It notes that the amount of data produced grows enormously every year due to new technologies and devices. Big data provides businesses with better sources of analysis and insights. Key trends discussed include the growth of open source tools like Hadoop and Spark, increased use of machine learning and predictive analytics, edge computing and analytics to process IoT data more efficiently, integration of big data and cloud computing, use of big data for cybersecurity, and growing demand for data science jobs. The conclusion states that big data will significantly impact businesses and 15% of IT organizations will move services to the cloud by 2021.
GfK Power to the iBrains: Identifying future consumer needs to anticipate dem...GfK
This document discusses strategies for retailers to engage future consumers, called "iBrains", who will make up 40% of consumers in major markets by 2020. It identifies that iBrains are digital natives who are mobile-first, social-driven, and value experiences over ownership. They browse intensively to find deals and are less loyal to brands. The document recommends that retailers shift from promoting new products to inspiring new experiences; start conversations about customers' lives instead of just telling brand stories; and make products better by incorporating customer input. Anticipating iBrain values and behaviors will be key to winning this important consumer group.
Conquering Connected Shoppers – GfK and REWE Digital at the 62nd Global Summi...GfK
Connected Shoppers are revolutionizing retail, and that’s true whatever sector you operate in. For consumer goods, the spotlight is on omnichannel. We believe the time is right for the complex grocery sector to be digitized. At the CGF Global Summit, together with REWE Digital, we discussed how you can maximize omnichannel today and tomorrow, profile different shopper segments, explain where to discover and reach them, and predict future trends. If you want to see if you are equipped to conquer the connected shopper in grocery, take a look at our presentation.
GfK - Insurance Incentives and Rewards in South AfricaGfK
Bradley Taylor investigates the insurance incentives and rewards in South Africa and what we can learn from the way rewards are used to drive loyalty and business in this competitive market.
GfK - The future of insurance: Hong Kong perspectiveGfK
Ronald Leung outlines what the future of insurance in this lucrative market might look like. It discusses the effects of technology on personalization and asks why insurance providers are being left behind.
Angelo Pierro introduce you to the technology trends in the insurance companies including examples of what winning tomorrow in this market can look like.
GfK and Visa: Reducing friction in the digital payment processGfK
Today’s established financial institutions are under pressure from three sources: the high expectations of Connected Consumers, the pace of technological change and innovation from new entrants. To remain relevant in the era of the smart home, connected car and mobile payments, these players must create compelling and easy-to-use digital financial products. Working with Visa, we’ve been investigating the central role that user experience (UX) has in ensuring success in this complex and competitive sector. To know more contact Tim Spenny (tim.spenny@gfk.com) and Lauren Zack (lauren.zack@gfk.com).
GfK - Go beyond the traditional metrics to measure the effectiveness of your ...GfK
Learn how to measure the effectiveness of your digital ad campaign on browser and in-app. Key is to go beyond the traditional metrics such as CPR and CPC to prove to your business that your campaign was successful thanks to strong KPI’s.
The document summarizes the findings of a GfK study on consumer perspectives on smart homes globally. It finds that while awareness and appeal of smart home technology is high, adoption remains low due to barriers like cost and privacy/security concerns. Additionally, the market lacks interoperability between different vendors' devices. The study suggests the smart home market will grow more slowly than expected until these challenges are addressed by creating easy to use and integrated solutions.
Find out the four key trends driving growth in the smartphone market based on our forecasting data. To access the full report, click on the download on slide 7.
User experience (UX) is a major selling point in the automotive industry. But most original equipment manufacturers (OEMs) and suppliers do not have a way of benchmarking UX.
We have developed and validated a groundbreaking new UX model in a global study that reveals how car owners benchmark each auto brand for user experience. It will show OEMs and suppliers what they should be focusing on the Human Machine Interface (HMI).
GfK - Creating a seamless life through the connected carGfK
1. The document summarizes the key findings of a global study conducted by GfK involving 5,800 consumers across 6 markets regarding their perceptions and preferences around connected car technologies.
2. The study found that most drivers currently experience positive emotions like happiness when driving. However, leading edge consumers who are early adopters and influencers are more open to new connected car technologies compared to general consumers.
3. Safety-oriented features like those that allow a car to communicate with other vehicles or integrate cameras are most appealing currently, although entertainment-focused and autonomous driving capabilities also interest consumers. Cultural differences across markets also influence perceptions.
The document discusses creating a connected consumer experience for retailers. It notes the new challenges facing retailers from more demanding and informed consumers, new competitors, and worldwide competition. The presentation argues that while the digital world is important, physical retail locations ("bricks") remain important for consumers' ability to see and touch products as well as for availability, after sales service, and convenience. It identifies cultural, backoffice, and economic challenges retailers face in connecting physical and digital experiences for consumers.
This document provides information about an organization called Streetwize that works with street children. It mentions that Streetwize operates in 22 countries and has had 50,000 contacts. It provides leadership training and workshops to street children to help develop their skills and mindset in a positive way. The organization aims to have a 360 degree impact and help street children through challenges of uncertainty and crisis.
This document discusses the transition from 2D to 3D organizations driven by global information waves and the rise of 3D learning and smarts. It describes how 2D schools and organizations limited talent and passion, treating people like "sheep." The emergence of 3D skills is creating an "extinction level event" for 2D approaches. Organizations are now searching for a new balance as they transition to the 3D age and adopt more innovative 3D models to survive increasing disruption in the global market.
This document discusses complaints and digital transformation. It notes that digital transformation has occurred in waves impacting industries like music, media, retail and more. It also provides data on how Belgians complain, with the majority complaining via email or phone. Some complain on social media for faster responses or more visibility. The document then discusses Frank's roadmap for digital loyalty at Mobile Vikings, noting they focus on younger customers and started on social media. It emphasizes creating connections, being transparent, involving communities and using real people with passion.
The document describes a study conducted by GfK to map the purchase journeys of 230 consumers looking to buy new smartphones and tablets. Researchers used a variety of online and offline methods, such as browser tracking, questionnaires, diaries, and observations to gather data on consumers' online and offline search behaviors and interactions with various touchpoints. The results provided insights into how consumers combine both online and offline search, the different websites visited, time spent conducting online research, and the reach and impact of various online and offline advertising and retail touchpoints along the purchase journey.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
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This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
3. For marketing deciders the
marriage of marketing, data and analytics
presents a tricky challenge as new buzzwords and
consequently solutions pop up literally every day
4. Innovation Trigger Peak of
Inflated
Expectations
Trough of
Disillusionment
Slope of Enlightenment Plateau of
Productivity
Smart Dust
4D Printing
General-Purpose Machine Intelligence
Augmented Reality
Natural-Language Question Answering
Enterprise Taxonomy and Ontology Management
Autonomous Vehicles
Cognitive Expert Advisors
Machine Learning
Software-Defined Security
Connected Home
Blockchain
Smart Robots
Micro Data Center
Gesture Controle Devices
IoT Platform
Commercial UAVs (Drones)
Affective Computing
Smart Data Discovery
Virtual Personal Assistants
Brain-Computer Interface
Conversational User Inferfaces
Volumetric Displays
Smart Workspace
Personal Analytics
Human Augmentation
Quantum Computing
Data Broker PaaS (dtxPaaS)
Neuromorphic Hardware
Context Brokering
802.11ax
Software-Defined Anything (SDx)
Nanotube Electornics
Expectations
Time
Less than 2 years 2 to 5 years 5 to 10 years More than 10 years Obsolete before plateauYears to mainstream adoption:
Virtual Reality
Source: Gartner (July2016) | http://www.gartner.com/newsroom/id/3412017