Business analytics can provide a major stimulus for transformational change. Yet neuroscience and psychology show us that people are typically not "wired" to engage with facts. Analytics leaders seeking to develop a data-driven culture must take positive steps to engage with emotions. What can we do to overcome these psychological resistance factors?
Key Challenges
Humans are "wired" with multiple mechanisms that inhibit their ability to engage with facts.
People's initial responses tend to be emotional rather than rational.
Being presented with evidence that contradicts existing beliefs and values can mean that positions become more entrenched, even when there is benefit to be derived from change.
Business benefits are mostly presented as benefits to the business only, rather than considering their effect on the beliefs and motivations of individuals.
Why to attend this webinar?
Information and Analytics leaders should attend this webinar to learn how to:
Connect emotionally with stakeholders, engage with both collective and personal benefits to increase engagement and ensure that there is both organizational and personal buy-in to decisions.
Avoid the psychological responses that inhibit engagement with data by communicating analytics outputs in ways that take such reactions into account.
Apply critical thinking when presenting analytics results, to overcome logical fallacies and decision biases.
How can you deliver real value with healthcare data analytics? Four things can help:
Tighten how you deliver information and insights.
Loosen the reins on who can be part of the conversation and contribute.
Create transparency into how data management and analytics works.
Paint a picture and tell a story with your insights.
...
And go do it! Don't just say you're going to do it.
I presented this at ICT Spring Europe 2015 in Luxembourg. The presentation highlights the way in which big data investments are not always delivering on their promise and why brands should consider taking a 'human-centred' approach to big data analytics.
Algorithms and the technology of personalisation finalColin Strong
This presentation was created for a Google working group meeting which explores the nature of the relationship between the consumer and the Internet. Presented at Google Offices, Berlin June 5th 2015.
Practical Data Strategies in the real world of poor Data QualityAndrew Patricio
My presentation for EDW 2017
Foundation
Data Effectiveness
Data Sophistication
Data Prioritization
Consistency, Relevancy, Accuracy
Data Quality Culture
Reporting platform
Managing Requests
Summary
The document discusses how analytics have become more widely accessible but advanced analytics requiring sophisticated skills have remained out of reach for most employees. It introduces IBM Watson Analytics as a solution that simplifies analytics so more people can access insights without technical skills. Watson Analytics removes obstacles like data preparation, addresses the skills gap through an intuitive interface, and leverages the cloud to make powerful analytics available anywhere.
Data is not facts: The impossibility of being unbiasedAndrew Patricio
The document discusses the difference between data and facts, and how personal biases can influence how data is interpreted. It notes that while the goal is to make conclusions based on data, data is not always completely valid or unbiased. Any personal judgments about what data is valid can inadvertently reinforce biases. It recommends increasing self-awareness of one's own emotional state and biases to recognize when personal judgment may be compromised and to be more open-minded towards alternative perspectives.
This document discusses strategies for effective data governance and data science. It argues that traditional data governance focuses only on symptoms and not root causes of data science failures. Effective data strategy requires understanding meaning in data, developing expert intuition over time, and allowing heterotopias for non-standard exploration. Data scientists must blend past and future methods during times of atemporality. Effective hiring strategies should sell mission, promote role crafting, and facilitate growth in a changing environment.
Shaping Tomorrow is the world’s first, multi-award winning, and only AI-driven, systems thinking model that delivers strategic foresight and anticipatory thinking in real-time.
How can you deliver real value with healthcare data analytics? Four things can help:
Tighten how you deliver information and insights.
Loosen the reins on who can be part of the conversation and contribute.
Create transparency into how data management and analytics works.
Paint a picture and tell a story with your insights.
...
And go do it! Don't just say you're going to do it.
I presented this at ICT Spring Europe 2015 in Luxembourg. The presentation highlights the way in which big data investments are not always delivering on their promise and why brands should consider taking a 'human-centred' approach to big data analytics.
Algorithms and the technology of personalisation finalColin Strong
This presentation was created for a Google working group meeting which explores the nature of the relationship between the consumer and the Internet. Presented at Google Offices, Berlin June 5th 2015.
Practical Data Strategies in the real world of poor Data QualityAndrew Patricio
My presentation for EDW 2017
Foundation
Data Effectiveness
Data Sophistication
Data Prioritization
Consistency, Relevancy, Accuracy
Data Quality Culture
Reporting platform
Managing Requests
Summary
The document discusses how analytics have become more widely accessible but advanced analytics requiring sophisticated skills have remained out of reach for most employees. It introduces IBM Watson Analytics as a solution that simplifies analytics so more people can access insights without technical skills. Watson Analytics removes obstacles like data preparation, addresses the skills gap through an intuitive interface, and leverages the cloud to make powerful analytics available anywhere.
Data is not facts: The impossibility of being unbiasedAndrew Patricio
The document discusses the difference between data and facts, and how personal biases can influence how data is interpreted. It notes that while the goal is to make conclusions based on data, data is not always completely valid or unbiased. Any personal judgments about what data is valid can inadvertently reinforce biases. It recommends increasing self-awareness of one's own emotional state and biases to recognize when personal judgment may be compromised and to be more open-minded towards alternative perspectives.
This document discusses strategies for effective data governance and data science. It argues that traditional data governance focuses only on symptoms and not root causes of data science failures. Effective data strategy requires understanding meaning in data, developing expert intuition over time, and allowing heterotopias for non-standard exploration. Data scientists must blend past and future methods during times of atemporality. Effective hiring strategies should sell mission, promote role crafting, and facilitate growth in a changing environment.
Shaping Tomorrow is the world’s first, multi-award winning, and only AI-driven, systems thinking model that delivers strategic foresight and anticipatory thinking in real-time.
The keynote speech discusses how organizations can better utilize large amounts of data to improve marketing decisions. While data analytics provide opportunities, many big data projects fail to meet expectations or improve decisions due to human biases. The speech recommends adopting lean startup principles of making hypotheses explicit, visualizing metrics, and implementing a build-measure-learn process to test ideas quickly. Combining both traditional analytical skills and big data approaches is important to effectively leverage data for smarter marketing decisions.
Whitepaper | The Impact of Valuing Employee Effort | Sapience AnalyticsSapience Analytics
Most organizations will agree that employees are working harder than ever before while also agreeing that employees are less engaged than ever before. What’s wrong with this picture? In this insightful whitepaper you can find an answer.
This whitepaper addresses 3 basic issues:
--Identifying if the employee’s efforts are in line with the value the organization desires
--Can knowing one’s productivity contribute to greater employee engagement?
--How can effort and value be measured?
How To Improve Profitability & Outperform Your Competition: the Guide to Data...A.J. Riedel
Find out how adopting data-driven decision-making can reduce your risk of making costly marketing and product mistakes and improve your product sell-through in this free E-Book.
This document provides a strategy for simplifying analytics. It recommends three steps: 1) Accelerate data to enable real-time insights, 2) Delegate work to analytics technologies like business intelligence, data visualization, machine learning, and 3) Recognize that each path to insights is unique and will require an outcome-driven approach tailored to the specific business problem and context. Simplifying the analytics process in this way can help organizations more effectively manage data and uncover insights.
This document discusses how advanced analytics and predictive modeling can help associations achieve strategic goals. It contrasts business intelligence with data science and explains how predictive modeling fits within an association's analytics framework. The document also provides examples of predictive models that associations could use, such as models to predict meeting attendance, purchasing likelihood, or long-term revenue from new members. Finally, it discusses how AFP has used predictive analytics to improve initiatives like customer journeys, onboarding programs, and community platforms.
This document discusses data-driven decision making and the role of emotions in decisions. It begins by introducing the topics to be covered: data creation, collation, information creation, collation, and decision making. It then discusses how data is created tactically but decisions require strategic data on options and impacts. Information technology helps integrate and filter data. Decisions inherently involve emotions as rewards and punishments shape choices even when data and options remain constant. Presenting options with emotional impacts, like consequences of inaction, can facilitate decisions. Understanding decision-makers' emotions allows effectively framing information to guide choices. Overall, the document argues decisions stem from both objective information and subjective emotions, so both must be considered to enable well-informed
This document discusses strategies for improving clinical trial site performance through quantifying site metrics and providing feedback. It recommends generating site-specific performance reports using data from the IVRS, calculating metrics like screening and enrollment rates. These reports should be shared with sites via email on a regular basis to start evidence-based conversations about performance. It also suggests using a web-based platform to provide ongoing feedback through features like leaderboards, awards, and educational resources in order to build relationships with sites and motivate improved performance. While data is important, it's also critical to understand the human factors influencing performance and support sites in addressing challenges.
Data analytics is used to make better business decisions by combining data and insights. There are four aspects to an effective data analytics framework: discovery, insights, actions, and outcomes. Discovery involves defining problems, developing hypotheses, and collecting relevant data. Insights are generated by exploring and analyzing the data. Actions link the insights to recommendations and plans. The desired outcomes are improved decisions and performance. Different types of analytics include descriptive (what happened), diagnostic (why), predictive (what could happen), and prescriptive (what should be done). Tools used include SQL, Hadoop, machine learning libraries, and optimization or simulation software.
Measuring Success introduces nonprofit professionals to proven techniques on how to move from anecdotal to data-driven decision making and steer your organization to success. Gain insights on how to focus your limited organizational time and energies on the issues that are supported by data instead of anecdotes. Learn techniques for using data to track and measure progress over time, report impact to stakeholders, and manage toward success.
P 02 ta_in_uw_transformation_2017_06_13_v5Vishwa Kolla
Text Analytics can be fun, useful and distracting. It is not just about the tools, but about how to use tools to drive business outcome. In this deck, you will get a sneak peak into some uses of text analytics in Life Insurance Transformation
The document summarizes a presentation on re-framing the well-being value proposition from a focus on health risk reduction to total well-being. It discusses how individual well-being encompasses five universal and interconnected elements - career, social, financial, physical, and community well-being. It also shows how engagement impacts physical health outcomes and disengagement impacts mental well-being, arguing for a broader view of well-being beyond just physical health risks.
This document summarizes a presentation on using analytics for better decision making at nonprofit organizations. The presentation discusses how nonprofits currently use some basic analytics like budgets and dashboards but have untapped potential to use data more extensively. It identifies common challenges to data utilization as collecting quality data, lacking expertise, technology and prioritizing time and money for analytics. The presentation provides examples of how benchmarking reveals data gaps and inconsistencies between systems. It emphasizes the value of tracking program and outcome data and client information.
Avoid organizationalmistakes by innovative thinkingSelf-employed
1. The document discusses 10 common mistakes organizations make with performance measures. These include relying solely on financial statements, only looking at monthly or quarterly results, setting goals without ways to measure them, using poor methods like brainstorming to select measures, overreliance on technology to fix measurement problems, using tables instead of graphs to report results, failing to identify relationships between measures, excluding staff from analysis and improvement, collecting too much useless data and not enough relevant data, and using measures solely to reward and punish individuals.
2. Key mistakes are focusing only on lagging financial indicators, short-term results, and goals without measurement; as well as poor methods for selecting measures, not understanding relationships between measures, and not
It seems the world is all fascinated with amazing insight from Big Data... but we all know what really matters is the VALUE unlocked from those insights...
Too often we assume that smart people will know what to do if the Masters of Data Science unloads new wisdom on the business. The reality is we have to empower the ultimate people who have to act on these new insights with processes and business levers that also smarter.
In this presentation, we explore what is the difference between insight and value... the difference between a finding that is interesting, and a finding that has impact.
The presentation captures a career of learnings in Big Data and Advanced Analytics as the Lead Partner who established and led Deloitte's Advanced Analytics practice in WA
In the past 5 years, many OSH professionals have begun promoting a substantially different approach to occupational safety and health that focuses on risk-based systems rather than compliance. This shift is occurring because compliance-focused programs were not fully addressing risks and injury rates had plateaued. The article provides 5 tips to help OSH professionals begin making this transition, including becoming experts in risk management, focusing discussions on risk reduction rather than regulations, promoting leading safety metrics, analyzing incident data to identify highest risks, and finding allies interested in risk-based approaches.
Change Management: The Secret to a Successful SAS® ImplementationThotWave
Whether you are deploying a new capability with SAS® or modernizing the tool set that people already use in your organization, change management is a valuable practice. Sharing the news of a change with employees can be a daunting task and is often put off until the last possible second. Organizations frequently underestimate the impact of the change, and the results of that miscalculation can be disastrous. Too often, employees find out about a change just before mandatory training and are expected to embrace it. But change management is far more than training. It is early and frequent communication, an inclusive discussion, encouraging and enabling the development of an individual, and facilitating learning before, during, and long after the change.
This paper not only showcases the importance of change management but also identifies key objectives for a purposeful strategy. We outline our experiences with both successful and not so successful organizational changes. We present best practices for implementing change management strategies and highlighting common gaps. For example, developing and engaging “Change Champions” from the beginning alleviates many headaches and avoids disruptions. Finally, we discuss how the overall company culture can either support or hinder the positive experience change management should be and how to engender support for formal change management in your organization.
Smart Data Webinar: Emerging Data Management OptionsDATAVERSITY
Everyone talks about the challenges of managing big data, but applications built for the next decade will need more than “bigger” and “faster” versions of the RDBMS systems that dominated at the end of the last century and updates to the NoSQL databases popularized at the beginning of this century. They will need tools that are optimized to manage streaming data and structures that map naturally to knowledge representations such as ontologies and taxonomies.
In this webinar, participants will learn:
Why graph database usage is growing rapidly and what to look for from vendors,
How transaction & analytic processing are converging in real time, and
How market leaders are building apps today with modern data management solutions, (short case studies from a variety of industries)
Animation has existed since prehistoric times, with one of the earliest examples being an 8-legged boar drawing in the Altamira caves over 10,000 years old. Early animation concepts included Egyptian wall drawings from 2000 BC depicting wrestlers in motion and Leonardo Da Vinci's illustrations of limbs in different positions. Animation was made possible by the persistence of vision, the phenomenon where the human eye retains an image for a fraction of a second after seeing it, first demonstrated in 1828. Early animation devices included the Thaumatrope in 1828 and the zoetrope in 1860, which used successive drawings to create the illusion of motion. The development of film cameras and projectors in the late 19th
Este documento habla sobre la composición bidimensional del color. Explica que el color produce sensaciones y sentimientos en nuestra percepción visual aunque no existe más allá de esta. Luego describe la armonía de color como combinaciones de tonos similares que mantienen parte de los mismos pigmentos, y el contraste de color como la diferenciación de colores por luminosidad o fondo.
The keynote speech discusses how organizations can better utilize large amounts of data to improve marketing decisions. While data analytics provide opportunities, many big data projects fail to meet expectations or improve decisions due to human biases. The speech recommends adopting lean startup principles of making hypotheses explicit, visualizing metrics, and implementing a build-measure-learn process to test ideas quickly. Combining both traditional analytical skills and big data approaches is important to effectively leverage data for smarter marketing decisions.
Whitepaper | The Impact of Valuing Employee Effort | Sapience AnalyticsSapience Analytics
Most organizations will agree that employees are working harder than ever before while also agreeing that employees are less engaged than ever before. What’s wrong with this picture? In this insightful whitepaper you can find an answer.
This whitepaper addresses 3 basic issues:
--Identifying if the employee’s efforts are in line with the value the organization desires
--Can knowing one’s productivity contribute to greater employee engagement?
--How can effort and value be measured?
How To Improve Profitability & Outperform Your Competition: the Guide to Data...A.J. Riedel
Find out how adopting data-driven decision-making can reduce your risk of making costly marketing and product mistakes and improve your product sell-through in this free E-Book.
This document provides a strategy for simplifying analytics. It recommends three steps: 1) Accelerate data to enable real-time insights, 2) Delegate work to analytics technologies like business intelligence, data visualization, machine learning, and 3) Recognize that each path to insights is unique and will require an outcome-driven approach tailored to the specific business problem and context. Simplifying the analytics process in this way can help organizations more effectively manage data and uncover insights.
This document discusses how advanced analytics and predictive modeling can help associations achieve strategic goals. It contrasts business intelligence with data science and explains how predictive modeling fits within an association's analytics framework. The document also provides examples of predictive models that associations could use, such as models to predict meeting attendance, purchasing likelihood, or long-term revenue from new members. Finally, it discusses how AFP has used predictive analytics to improve initiatives like customer journeys, onboarding programs, and community platforms.
This document discusses data-driven decision making and the role of emotions in decisions. It begins by introducing the topics to be covered: data creation, collation, information creation, collation, and decision making. It then discusses how data is created tactically but decisions require strategic data on options and impacts. Information technology helps integrate and filter data. Decisions inherently involve emotions as rewards and punishments shape choices even when data and options remain constant. Presenting options with emotional impacts, like consequences of inaction, can facilitate decisions. Understanding decision-makers' emotions allows effectively framing information to guide choices. Overall, the document argues decisions stem from both objective information and subjective emotions, so both must be considered to enable well-informed
This document discusses strategies for improving clinical trial site performance through quantifying site metrics and providing feedback. It recommends generating site-specific performance reports using data from the IVRS, calculating metrics like screening and enrollment rates. These reports should be shared with sites via email on a regular basis to start evidence-based conversations about performance. It also suggests using a web-based platform to provide ongoing feedback through features like leaderboards, awards, and educational resources in order to build relationships with sites and motivate improved performance. While data is important, it's also critical to understand the human factors influencing performance and support sites in addressing challenges.
Data analytics is used to make better business decisions by combining data and insights. There are four aspects to an effective data analytics framework: discovery, insights, actions, and outcomes. Discovery involves defining problems, developing hypotheses, and collecting relevant data. Insights are generated by exploring and analyzing the data. Actions link the insights to recommendations and plans. The desired outcomes are improved decisions and performance. Different types of analytics include descriptive (what happened), diagnostic (why), predictive (what could happen), and prescriptive (what should be done). Tools used include SQL, Hadoop, machine learning libraries, and optimization or simulation software.
Measuring Success introduces nonprofit professionals to proven techniques on how to move from anecdotal to data-driven decision making and steer your organization to success. Gain insights on how to focus your limited organizational time and energies on the issues that are supported by data instead of anecdotes. Learn techniques for using data to track and measure progress over time, report impact to stakeholders, and manage toward success.
P 02 ta_in_uw_transformation_2017_06_13_v5Vishwa Kolla
Text Analytics can be fun, useful and distracting. It is not just about the tools, but about how to use tools to drive business outcome. In this deck, you will get a sneak peak into some uses of text analytics in Life Insurance Transformation
The document summarizes a presentation on re-framing the well-being value proposition from a focus on health risk reduction to total well-being. It discusses how individual well-being encompasses five universal and interconnected elements - career, social, financial, physical, and community well-being. It also shows how engagement impacts physical health outcomes and disengagement impacts mental well-being, arguing for a broader view of well-being beyond just physical health risks.
This document summarizes a presentation on using analytics for better decision making at nonprofit organizations. The presentation discusses how nonprofits currently use some basic analytics like budgets and dashboards but have untapped potential to use data more extensively. It identifies common challenges to data utilization as collecting quality data, lacking expertise, technology and prioritizing time and money for analytics. The presentation provides examples of how benchmarking reveals data gaps and inconsistencies between systems. It emphasizes the value of tracking program and outcome data and client information.
Avoid organizationalmistakes by innovative thinkingSelf-employed
1. The document discusses 10 common mistakes organizations make with performance measures. These include relying solely on financial statements, only looking at monthly or quarterly results, setting goals without ways to measure them, using poor methods like brainstorming to select measures, overreliance on technology to fix measurement problems, using tables instead of graphs to report results, failing to identify relationships between measures, excluding staff from analysis and improvement, collecting too much useless data and not enough relevant data, and using measures solely to reward and punish individuals.
2. Key mistakes are focusing only on lagging financial indicators, short-term results, and goals without measurement; as well as poor methods for selecting measures, not understanding relationships between measures, and not
It seems the world is all fascinated with amazing insight from Big Data... but we all know what really matters is the VALUE unlocked from those insights...
Too often we assume that smart people will know what to do if the Masters of Data Science unloads new wisdom on the business. The reality is we have to empower the ultimate people who have to act on these new insights with processes and business levers that also smarter.
In this presentation, we explore what is the difference between insight and value... the difference between a finding that is interesting, and a finding that has impact.
The presentation captures a career of learnings in Big Data and Advanced Analytics as the Lead Partner who established and led Deloitte's Advanced Analytics practice in WA
In the past 5 years, many OSH professionals have begun promoting a substantially different approach to occupational safety and health that focuses on risk-based systems rather than compliance. This shift is occurring because compliance-focused programs were not fully addressing risks and injury rates had plateaued. The article provides 5 tips to help OSH professionals begin making this transition, including becoming experts in risk management, focusing discussions on risk reduction rather than regulations, promoting leading safety metrics, analyzing incident data to identify highest risks, and finding allies interested in risk-based approaches.
Change Management: The Secret to a Successful SAS® ImplementationThotWave
Whether you are deploying a new capability with SAS® or modernizing the tool set that people already use in your organization, change management is a valuable practice. Sharing the news of a change with employees can be a daunting task and is often put off until the last possible second. Organizations frequently underestimate the impact of the change, and the results of that miscalculation can be disastrous. Too often, employees find out about a change just before mandatory training and are expected to embrace it. But change management is far more than training. It is early and frequent communication, an inclusive discussion, encouraging and enabling the development of an individual, and facilitating learning before, during, and long after the change.
This paper not only showcases the importance of change management but also identifies key objectives for a purposeful strategy. We outline our experiences with both successful and not so successful organizational changes. We present best practices for implementing change management strategies and highlighting common gaps. For example, developing and engaging “Change Champions” from the beginning alleviates many headaches and avoids disruptions. Finally, we discuss how the overall company culture can either support or hinder the positive experience change management should be and how to engender support for formal change management in your organization.
Smart Data Webinar: Emerging Data Management OptionsDATAVERSITY
Everyone talks about the challenges of managing big data, but applications built for the next decade will need more than “bigger” and “faster” versions of the RDBMS systems that dominated at the end of the last century and updates to the NoSQL databases popularized at the beginning of this century. They will need tools that are optimized to manage streaming data and structures that map naturally to knowledge representations such as ontologies and taxonomies.
In this webinar, participants will learn:
Why graph database usage is growing rapidly and what to look for from vendors,
How transaction & analytic processing are converging in real time, and
How market leaders are building apps today with modern data management solutions, (short case studies from a variety of industries)
Animation has existed since prehistoric times, with one of the earliest examples being an 8-legged boar drawing in the Altamira caves over 10,000 years old. Early animation concepts included Egyptian wall drawings from 2000 BC depicting wrestlers in motion and Leonardo Da Vinci's illustrations of limbs in different positions. Animation was made possible by the persistence of vision, the phenomenon where the human eye retains an image for a fraction of a second after seeing it, first demonstrated in 1828. Early animation devices included the Thaumatrope in 1828 and the zoetrope in 1860, which used successive drawings to create the illusion of motion. The development of film cameras and projectors in the late 19th
Este documento habla sobre la composición bidimensional del color. Explica que el color produce sensaciones y sentimientos en nuestra percepción visual aunque no existe más allá de esta. Luego describe la armonía de color como combinaciones de tonos similares que mantienen parte de los mismos pigmentos, y el contraste de color como la diferenciación de colores por luminosidad o fondo.
The document provides an agenda for an English lesson that includes identifying and memorizing vocabulary about materials and objects, reviewing questions in the passive voice, and practicing speaking and listening by asking about objects. Students will ask yes/no and WH-questions about objects and describe objects. The lesson focuses on vocabulary, grammar, speaking, and listening skills related to materials, objects, and asking questions.
This thesis investigated Tobacco streak virus (TSV), which was found to cause a previously unknown sunflower necrosis disorder in central Queensland, Australia. The research identified two distinct TSV strains (TSV-parthenium and TSV-crownbeard) through genetic characterization. Field studies showed parthenium and crownbeard weed species act as major symptomless hosts of the respective TSV strains. Both strains were found to be seed and thrips-transmitted. The research also evaluated sunflower hybrid tolerance to TSV and found seasonal disease variation correlated with rainfall. This work provides insights into the diversity, epidemiology and management of TSV in Australia.
Three New England states - Connecticut, Massachusetts, and Maine - announced they will sue the Environmental Protection Agency over its determination that it lacks legal authority to regulate carbon dioxide emissions from vehicles under the Clean Air Act. The states argue that EPA does have authority to regulate these emissions. They will challenge EPA's decision in federal court, claiming it contradicts earlier EPA statements and testimony acknowledging that greenhouse gas emissions endanger public health. Environmental groups had previously requested that EPA regulate vehicle CO2 emissions, but EPA denied that request in August, asserting that Congress did not give it authority to do so.
The Defend Trade Secrets Act of 2016 (DTSA) creates a federal civil cause of action for trade secret misappropriation and allows companies to file lawsuits in federal court. It expands protection of valuable intellectual property like customer lists, source code, formulas and manufacturing methods. The new law does not replace state laws but provides an additional avenue for protection and enforcement of trade secrets. Employers should notify employees about whistleblower protections under the DTSA and implement security measures like non-disclosure agreements and access controls to protect valuable proprietary information.
(1) This research evaluates the quality of PhD programs at Baghdad University and Al-Mustansiriyah University based on student assessments using the Quality Function Deployment (QFD) technique.
(2) QFD was used to build a House of Quality relating (13) student requirements to (12) quality attributes. The analysis determined the lowest quality attributes that are most important for satisfying student requirements.
(3) The document provides background on QFD, describing its origins and spread among major companies. It outlines the basic QFD process and matrices used to relate customer requirements to technical requirements.
How to Write an Argumentative Essay Step By Step - Gudwriter. A Useful Guide On How To Write A Classical Argument Essay In Several .... Short Position Paper Examples - Argument Paper For Hypothetical .... 007 How To Write Claim For An Argumentative Essay Example .... Of An Argumentive Essay - Opinion of professionals | Argumentative .... 017 Proposal Argument Essay Examples Example Research Pics Photos .... 10+ Argumentative Essay Outline Templates - PDF. Sample Argumentative Essay. 009 Essay Example Position Argument ~ Thatsnotus. Argumentative essay example short Truth or Consequences .... 021 Essay Introduction Paragraph Example Argumentative Format .... 004 Argument Essay Format Example Structure For Argumentative Body ....
Slide share Hyper-Decision Making - Short VersionDr. Ted Marra
The new imperative for organisational success will be 'hyper-decision making'. Gain insights into executive research around decision making; the concept of 'optimal' decision; the costs of lost opportunity associated with decision making; the factors that determine your organisation's 'decision intelligence quotient'; the drivers of 'risk'; what a systematic, integrated and comprehensive decision making process looks like; and more! Enjoy!
Collaborative Analytics & Insights: Uniting Strategy with Organizational Inte...Arik Johnson
The document discusses collaborative analytics and insights, specifically how uniting organizational strategy and intelligence can help anticipate industry changes. It notes key business trends like human capital/collaboration, governance/risk oversight, and business model disruption are driving intelligence evolution. Intelligence must engage the entire workforce in collaborative sensing to anticipate changes. The document provides examples of "key intelligence topics" that can be used in interviews with decision-makers to discuss strategic issues, key players, and early warnings. It also discusses wargaming examples and using tools like decision/selection maps to clarify customer needs and assess competitors.
Authentic state-of-the-art articles are what make the PECB Insights Magazine an unequaled source of information and inspiration.
In this issue, each story is a unique discovery; a meticulous blend of the informative and artistic dimensions in a matrix, the keyword of which is interactivity. The combination of the best of leadership, technology, business & leisure, travel and much more inspire transformation and invite the reader to spend free time tastefully. This magazine edition is packed with straight-forward, yet sophisticated pieces related to industry trends, from Artificial Intelligence, to 3d printing and traveling experiences which take your breath away through the exhilarating experiences portrayed by personal stories.
Our readers are at the top of their game, and they drive us to be at the top of ours!
Humanizing Big Data: The Key to Actionable Customer Journey AnalyticsRocketSource
The ability to gather and act on Big Data has changed our world. For companies, this influx of information is an opportunity to understand consumers on an unprecedented level. But there's a big difference between collecting disparate data points and connecting with consumers through journey analytics.
12º Insurance Service Meeting - Cassio DreyfussCNseg
The document discusses the digital future and digital transformation. It notes that the digital future will see people digitally connected to all domains of their lives, both personal and professional. It states that digital transformation is not just "more of the same" but fundamentally different, providing education as an example where technology could allow for personalized, remote, and data-driven learning. The document emphasizes that digital transformation is ultimately about information - how it flows and is used - and that the changes will impact work patterns, organizations, and relationships. It frames digital transformation as a journey that requires engaging people, changing mindsets, leveraging technology, and rethinking roles.
Partnering with Health Systems: Potholes and Pitfalls on the road from Custom...Levi Shapiro
Partnering with Health Systems: Potholes and Pitfalls on the road from Customer to Partner. Presentation by Dr. Ilan Rubinfeld, Associate CMIO, Henry Ford Health System.
The document discusses the inherent differences between startups and healthcare systems that can lead to conflict and friction in partnerships. It notes that startups are nimble with high risk tolerance and short horizons, while healthcare systems are slow, risk-averse, and have long planning horizons. The document provides strategies for startups and healthcare systems to find common ground and run successful projects, including understanding each other's perspectives, conducting realistic assessments of costs and timelines, and focusing on mutual interests rather than positions.
Safety and Social Media Dia webinar 12 sep2013 Michael Ibara
This is a webinar version of a talk I originally gave at a DIA event in Wash DC. I've used different examples from my original talk but the theme is the same.
Data is Worthless if You Don’t Communicate ItTanayKarnik1
This document discusses the importance of effectively communicating data and insights from data analysis. It notes that data is worthless if not communicated, and that research findings will not speak for themselves and need to be disseminated through various outlets. Some key ways to communicate about data analysis projects are outlined, including understanding the business problem, measuring impact, available data, hypotheses, solutions, and impact of solutions. The document stresses that audiences care most about results and implications, so the communication should tell a good story with the data. Managers especially need to better understand and communicate quantitative analysis and what the numbers mean.
Leaders may think that awareness programs are suitable for addressing unconscious bias, but they are just the start. Raising awareness of unconscious bias through presentations and tests does not actually change behaviors or outcomes. To effectively address unconscious bias, organizations need to focus on changing behaviors through shared knowledge, language to discuss biases, and structural approaches like requiring diversity in hiring panels. The most effective strategies are concrete rules and policies that change outcomes by increasing minority applicants and representation, rather than just focusing on awareness.
7 excellent reasons why statistics are important statsworkStats Statswork
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P 01 ins_analytics_ai_in_life_case_studies_2017_10_16_v12Vishwa Kolla
1. AI is helping life insurance companies improve processes like underwriting and claims handling by making them more efficient.
2. One case study showed how using consented health data and predictive models allowed underwriting decisions to be made in hours instead of weeks.
3. Another case study demonstrated how combining human and machine pattern detection helped identify suspicious claims patterns that could indicate fraud.
Digital Health Success Stories (and Failures) Report - Part 2Tom Parsons
Part 2 of our report looks closely at some of the high profile failures to date in order to highlight warnings signs for projects and collaborations in the future. You’ll hear from Skip Fleshman, General Partner at Asset Management Ventures, about his perspective on the enormous investment being pumped into the market and how it should be managed. You’ll get an insider view from Cure Forward and Imperial College Health Partners about some of the reasons behind failures they have experienced and what we can learn from them. And through 2 case studies, you’ll learn more about how transparent and accurate results and trials are integral to ongoing development and success.
The document discusses different approaches to compliance and ethics programs. It argues that a dynamic approach using behavioral science, data, and positive language is more effective than a traditional prescriptive approach. A dynamic approach frames compliance in a rational, scientific context and emphasizes the benefits of compliance rather than penalties of non-compliance. It also tailors messaging to different levels in an organization by understanding their unique motivations and objectives. An effective program requires understanding an organization's business and adapting to motivate long-term, meaningful change.
The document discusses different approaches to compliance and ethics programs. It argues that a dynamic approach using behavioral science, data, and positive language is more effective than a traditional prescriptive approach. A dynamic approach frames compliance in a rational, scientific context and emphasizes the benefits of compliance rather than penalties of non-compliance. It also tailors messaging to different levels in an organization by understanding their unique motivations and objectives. An effective program requires understanding an organization's business and adapting to motivate long-term, meaningful change.
Finding Actionable Insights from Healthcare's Big DataMedullan
This webinar covers how to:
- understand ways to prioritize your business drivers
- analyze your data and align opportunities (cost, reimbursement, risk) to maximize impact
- understand your target hyper-segment down to the member level
- identify higher cost segments and behaviors that would benefit from digital intervention
- learn ways to take action now
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen?
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
1) The document discusses best practices for data protection on Google Cloud, including setting data policies, governing access, classifying sensitive data, controlling access, encryption, secure collaboration, and incident response.
2) It provides examples of how to limit access to data and sensitive information, gain visibility into where sensitive data resides, encrypt data with customer-controlled keys, harden workloads, run workloads confidentially, collaborate securely with untrusted parties, and address cloud security incidents.
3) The key recommendations are to protect data at rest and in use through classification, access controls, encryption, confidential computing; securely share data through techniques like secure multi-party computation; and have an incident response plan to quickly address threats.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
The Role of White Label Bookkeeping Services in Supporting the Growth and Sca...YourLegal Accounting
Effective financial management is important for expansion and scalability in the ever-changing US business environment. White Label Bookkeeping services is an innovative solution that is becoming more and more popular among businesses. These services provide a special method for managing financial duties effectively, freeing up companies to concentrate on their main operations and growth plans. We’ll look at how White Label Bookkeeping can help US firms expand and develop in this blog.
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𝐔𝐧𝐯𝐞𝐢𝐥 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐄𝐧𝐞𝐫𝐠𝐲 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐰𝐢𝐭𝐡 𝐍𝐄𝐖𝐍𝐓𝐈𝐃𝐄’𝐬 𝐋𝐚𝐭𝐞𝐬𝐭 𝐎𝐟𝐟𝐞𝐫𝐢𝐧𝐠𝐬
Explore the details in our newly released product manual, which showcases NEWNTIDE's advanced heat pump technologies. Delve into our energy-efficient and eco-friendly solutions tailored for diverse global markets.
Enhancing Adoption of AI in Agri-food: IntroductionCor Verdouw
Introduction to the Panel on: Pathways and Challenges: AI-Driven Technology in Agri-Food, AI4Food, University of Guelph
“Enhancing Adoption of AI in Agri-food: a Path Forward”, 18 June 2024
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The Steadfast and Reliable Bull: Taurus Zodiac Signmy Pandit
Explore the steadfast and reliable nature of the Taurus Zodiac Sign. Discover the personality traits, key dates, and horoscope insights that define the determined and practical Taurus, and learn how their grounded nature makes them the anchor of the zodiac.
Cover Story - China's Investment Leader - Dr. Alyce SUmsthrill
In World Expo 2010 Shanghai – the most visited Expo in the World History
https://www.britannica.com/event/Expo-Shanghai-2010
China’s official organizer of the Expo, CCPIT (China Council for the Promotion of International Trade https://en.ccpit.org/) has chosen Dr. Alyce Su as the Cover Person with Cover Story, in the Expo’s official magazine distributed throughout the Expo, showcasing China’s New Generation of Leaders to the World.
During the budget session of 2024-25, the finance minister, Nirmala Sitharaman, introduced the “solar Rooftop scheme,” also known as “PM Surya Ghar Muft Bijli Yojana.” It is a subsidy offered to those who wish to put up solar panels in their homes using domestic power systems. Additionally, adopting photovoltaic technology at home allows you to lower your monthly electricity expenses. Today in this blog we will talk all about what is the PM Surya Ghar Muft Bijli Yojana. How does it work? Who is eligible for this yojana and all the other things related to this scheme?
Presentation by Herman Kienhuis (Curiosity VC) on Investing in AI for ABS Alu...Herman Kienhuis
Presentation by Herman Kienhuis (Curiosity VC) on developments in AI, the venture capital investment landscape and Curiosity VC's approach to investing, at the alumni event of Amsterdam Business School (University of Amsterdam) on June 13, 2024 in Amsterdam.
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Unlocking WhatsApp Marketing with HubSpot: Integrating Messaging into Your Ma...Niswey
50 million companies worldwide leverage WhatsApp as a key marketing channel. You may have considered adding it to your marketing mix, or probably already driving impressive conversions with WhatsApp.
But wait. What happens when you fully integrate your WhatsApp campaigns with HubSpot?
That's exactly what we explored in this session.
We take a look at everything that you need to know in order to deploy effective WhatsApp marketing strategies, and integrate it with your buyer journey in HubSpot. From technical requirements to innovative campaign strategies, to advanced campaign reporting - we discuss all that and more, to leverage WhatsApp for maximum impact. Check out more details about the event here https://events.hubspot.com/events/details/hubspot-new-delhi-presents-unlocking-whatsapp-marketing-with-hubspot-integrating-messaging-into-your-marketing-strategy/