Big Data for small business transform your business into more efficient and smarter operation. Stay ahead of the game and take advantage of Big data analytics for small business to now how can big data help small businesses.
Ppt bigdataanalyticsfinanceprofessionals-big data, business analytics and fin...Aravindharamanan S
This document summarizes a presentation about big data, business analytics, and how finance professionals can exploit these tools. The presenter has global experience working with major corporations. They discuss key concepts like understanding big data, exploring business analytics, and how finance can use these tools. Finance needs to build analytical capabilities and get value from both internal and external data sources. Business analytics can help make sense of large and complex data. The roles of finance professionals are expanding from traditional financial analysis to providing insights using a variety of analytical tools and techniques.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
The document discusses eBay's use of data and analytics. It notes that eBay sees 800 million items traded across 220 countries, generating $82 billion in merchandise annually. It also details some of eBay's big data metrics, like 350 million searches and 500 million viewed items daily. The rest of the document outlines eBay's approach to using small, centralized analytics teams that work across business units to deliver strategic insights and operational efficiencies through a matrix structure. It emphasizes starting with a clear vision, aligning work to business priorities, and choosing high-impact areas to support in order to help the business.
This document discusses how data analytics can help businesses overcome challenges and gain insights. It begins by explaining why businesses need to change by embracing new data-driven paradigms. It then outlines some common challenges like a lack of digital strategy or perceived complexity. The document proposes addressing these challenges through a CLERA approach: clarify needs, list data requirements, extract insights, adopt agile solutions, and replicate successes. It provides several use cases of applying classification, visualization, detection, and prediction techniques to gain insights from data in areas like reviews, sales, foot traffic, and fraud. Finally, it concludes that accounting and analytics must become integrated and businesses should embrace transformation to turn data into meaningful insights.
Financial analytics can help companies answer important strategic questions by providing forward-looking insights from large amounts of internal and external data. It moves beyond traditional financial reporting to help shape business strategy and improve real-time decision making. By analyzing risks, processes, investments, customer profitability, and other factors, financial analytics helps optimize profits and predict future impacts on key business drivers and stock price. It arms finance leaders with visual tools to understand complex information and partner more strategically with other areas of the business.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Ppt bigdataanalyticsfinanceprofessionals-big data, business analytics and fin...Aravindharamanan S
This document summarizes a presentation about big data, business analytics, and how finance professionals can exploit these tools. The presenter has global experience working with major corporations. They discuss key concepts like understanding big data, exploring business analytics, and how finance can use these tools. Finance needs to build analytical capabilities and get value from both internal and external data sources. Business analytics can help make sense of large and complex data. The roles of finance professionals are expanding from traditional financial analysis to providing insights using a variety of analytical tools and techniques.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
The document discusses eBay's use of data and analytics. It notes that eBay sees 800 million items traded across 220 countries, generating $82 billion in merchandise annually. It also details some of eBay's big data metrics, like 350 million searches and 500 million viewed items daily. The rest of the document outlines eBay's approach to using small, centralized analytics teams that work across business units to deliver strategic insights and operational efficiencies through a matrix structure. It emphasizes starting with a clear vision, aligning work to business priorities, and choosing high-impact areas to support in order to help the business.
This document discusses how data analytics can help businesses overcome challenges and gain insights. It begins by explaining why businesses need to change by embracing new data-driven paradigms. It then outlines some common challenges like a lack of digital strategy or perceived complexity. The document proposes addressing these challenges through a CLERA approach: clarify needs, list data requirements, extract insights, adopt agile solutions, and replicate successes. It provides several use cases of applying classification, visualization, detection, and prediction techniques to gain insights from data in areas like reviews, sales, foot traffic, and fraud. Finally, it concludes that accounting and analytics must become integrated and businesses should embrace transformation to turn data into meaningful insights.
Financial analytics can help companies answer important strategic questions by providing forward-looking insights from large amounts of internal and external data. It moves beyond traditional financial reporting to help shape business strategy and improve real-time decision making. By analyzing risks, processes, investments, customer profitability, and other factors, financial analytics helps optimize profits and predict future impacts on key business drivers and stock price. It arms finance leaders with visual tools to understand complex information and partner more strategically with other areas of the business.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Dashboards have become a powerful tool for Financial Planning and Analysis (FP&A) professionals to share insight. When designed correctly, they deliver a clear message on what’s working and what’s not, and the actions to take to fix the issue. Technology now enables us to create dashboards in minutes, allowing us to share information in ways we could never before.
The big question has moved from “How do we create dashboards?” to “How do we harness this powerful tool to drive business behavior?”
Panelists from a large company, a small company and a software consulting firm will share insights on how their companies are tackling the arena of Big Data and how to leverage a variety of data sources for strategic decision-making.
FP&A: Innovations in Financial Analytics to Support Organic Growth and Busine...James Myers
Google overhauled its finance department by hiring engineers and business intelligence professionals instead of additional finance practitioners in 2008-2009. Google then stopped hiring for finance altogether in 2009, determining any growth would be emergency-based only. Over time, Google reduced its finance workforce yet maintained productivity by eliminating unnecessary processes, automating others, and simplifying what remained. The company adheres to the Six Sigma methodology of constant improvement.
Stop Searching for That Elusive Data ScientistTanayKarnik1
The document summarizes an article that argues organizations should stop searching for elusive data scientists and instead form small cross-functional data teams. It notes that true data scientists are rare and bring more than just technical skills. While some individuals have some statistical and software knowledge, they may do more harm than good. The document recommends seed-funding small teams explicitly tasked with short-term, measurable data-driven projects. The goal is to spread data capabilities throughout an organization rather than focus on technical experts alone. Forming these teams can help organizations gain insights while they work to cultivate long-term internal data science skills.
While companies are investing heavily in data analytics technologies, many are not seeing significant returns because they lack the capabilities to properly analyze data and implement changes based on insights. For businesses to truly benefit from big data, managers must focus first on using data to guide operational decisions, establish processes for cleaning and analyzing data, and drive cultural changes to support evidence-based decision making. Only after achieving these foundations can companies hope to leverage more advanced big data technologies and analytics to gain competitive advantages.
This document discusses how advanced analytics and big data have become top priorities for companies. It argues that big data has the potential to transform businesses and deliver major performance gains. However, companies need to carefully define a pragmatic strategy for using data and analytics, focusing on how to make better decisions. The key is having a clear strategy for how to use data to compete and deploying the right IT architecture and analytical capabilities. Past failures with CRM show that analytics initiatives need to align with companies' processes and decision-making.
Big data and analytics have become increasingly important in the corporate world. Venture capital investments in big data are growing exponentially. Research from MIT shows analytics can increase productivity by 5-6%. However, many companies are unsure how to implement analytics effectively. The document outlines three key capabilities for exploring big data: identify the right data sources, build advanced analytics models, and transform the organization to make better decisions based on data and models. Mastering these skills can help companies gain a competitive advantage.
The document discusses how cognitive computing and artificial intelligence are disrupting various industries by enabling non-traditional business models. It provides examples of the world's largest taxi, accommodation, retailer, and media companies that own no vehicles, real estate, inventory, or create content, respectively. The document advocates that companies leverage cognitive computing to gain insights from vast amounts of new data through predictive, descriptive, and cognitive capabilities. It outlines steps to become a cognitive business through developing a strategy, extending analytics with cognitive, moving to cognitive cloud services, building cognitive infrastructure, and adopting cognitive security.
This document discusses different perspectives on big data and outlines strategies for adopting and utilizing big data. It presents big data as trifurcated among plumbing/infrastructure, networks/security, and task development. It then outlines curves showing the evolution from spreadsheets to accelerated decision making as big data is accepted and utilized, with the goal of establishing an ecosystem where data strategy is separate from IT and knowledge workers are maximized.
The document discusses challenges with hiring data scientists and suggests alternative approaches. It recommends empowering small cross-functional data-oriented teams explicitly tasked with delivering measurable business benefits. This builds internal data capabilities rather than just hiring expertise. It also stresses the importance of making data science a cultural value throughout the organization so that all employees understand basic principles and practices of data science.
Data analytics for the mid-market: myth vs. realityDeloitte Canada
This document discusses 5 myths that prevent mid-market companies from making smarter decisions using data analytics. The myths are that they are not big enough to benefit, they just need more data, it is IT's responsibility, they are not equipped for it, and it won't provide new insights. The realities are that analytics levels the playing field, visualization tools make existing data more useful, analytics requires business leadership partnering with IT, starting small using cloud solutions is possible, and having a vision and strategy is key to realizing value from analytics.
Big Data Real Time Marketring Content Trends Chase McMichael
The document discusses how big data can provide real-time business intelligence. It notes that with real-time comes real-time problems where intelligence and adaptive data management is required. It also discusses three aspects of big data and how big data is changing business and IT, with mobile use and cloud computing driving big data growth. The document emphasizes that big data analysis requires a mix of data collection, organization, and insights to provide strategic and tactical intelligence for brands.
Big Data: Implications for Marketing and StrategyC.K. Kumar
This document discusses big data and its impact on strategy and marketing. It begins with definitions of big data and introduces some key principles. Some differences between big data and small data are outlined. The document then discusses the big data value chain and workflow. It provides examples of how Target and EGI have used big data successfully. Finally, it discusses how small and medium businesses can leverage big data and provides some key takeaways.
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
This webinar discussed the purpose of data analytics and how it can be a light in the darkness for your organization to make better decisions for the future. The webinar covered the purpose of data analysis and its definition, the fundamental steps to take to perform data analysis to problem solve, and closed with next steps that attendees can take to further develop data analysis and business intelligence within their organizations.
During this webinar, attendees learned about the following:
- How data analytics functions to help your organization improve.
- The process for using data analytics to solve problems.
- Next steps to take to build data analysis within your organization.
The document discusses business analytics and how it was used by the Cincinnati Zoo and Botanical Garden to increase revenue and attendance. Specifically, it allowed the zoo to optimize food outlet operations, eliminate underperforming products, and use visitor data to target marketing to increase attendance by 4.2%. In general, business analytics involves using data, analytics, and technology to help managers make better fact-based decisions to improve various business operations and outcomes.
Data-Analytics-Resource-updated for analysisBhavinGada5
Data analytics is the analysis of large volumes of data to draw insights. It is important for cost reduction, faster decision making, revenue growth, and risk management. There are four main types: descriptive analyzes what happened, diagnostic analyzes why it happened, predictive analyzes what will happen, and prescriptive recommends actions. Data analytics helps financial reporting and auditing through risk understanding, process improvements, and continuous monitoring. Businesses use analytics for insights to transform models and gain deeper customer insights. While investment in analytics is widespread, cultural challenges of people and processes are a larger barrier than technology.
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Welcome to the Chief Analytics Officer Forum Europe
On 7th – 9th March 2016, over 80 Chief Analytics Officers and senior analytics leaders met in London for intimate, top-level discussions; dissecting the role of the CAO, exploring innovative case studies and addressing mutual cross-industry challenges. To learn more, visit http://www.caoforumeurope.com/
This event is organised by http://coriniumintelligence.com/
Dashboards have become a powerful tool for Financial Planning and Analysis (FP&A) professionals to share insight. When designed correctly, they deliver a clear message on what’s working and what’s not, and the actions to take to fix the issue. Technology now enables us to create dashboards in minutes, allowing us to share information in ways we could never before.
The big question has moved from “How do we create dashboards?” to “How do we harness this powerful tool to drive business behavior?”
Panelists from a large company, a small company and a software consulting firm will share insights on how their companies are tackling the arena of Big Data and how to leverage a variety of data sources for strategic decision-making.
FP&A: Innovations in Financial Analytics to Support Organic Growth and Busine...James Myers
Google overhauled its finance department by hiring engineers and business intelligence professionals instead of additional finance practitioners in 2008-2009. Google then stopped hiring for finance altogether in 2009, determining any growth would be emergency-based only. Over time, Google reduced its finance workforce yet maintained productivity by eliminating unnecessary processes, automating others, and simplifying what remained. The company adheres to the Six Sigma methodology of constant improvement.
Stop Searching for That Elusive Data ScientistTanayKarnik1
The document summarizes an article that argues organizations should stop searching for elusive data scientists and instead form small cross-functional data teams. It notes that true data scientists are rare and bring more than just technical skills. While some individuals have some statistical and software knowledge, they may do more harm than good. The document recommends seed-funding small teams explicitly tasked with short-term, measurable data-driven projects. The goal is to spread data capabilities throughout an organization rather than focus on technical experts alone. Forming these teams can help organizations gain insights while they work to cultivate long-term internal data science skills.
While companies are investing heavily in data analytics technologies, many are not seeing significant returns because they lack the capabilities to properly analyze data and implement changes based on insights. For businesses to truly benefit from big data, managers must focus first on using data to guide operational decisions, establish processes for cleaning and analyzing data, and drive cultural changes to support evidence-based decision making. Only after achieving these foundations can companies hope to leverage more advanced big data technologies and analytics to gain competitive advantages.
This document discusses how advanced analytics and big data have become top priorities for companies. It argues that big data has the potential to transform businesses and deliver major performance gains. However, companies need to carefully define a pragmatic strategy for using data and analytics, focusing on how to make better decisions. The key is having a clear strategy for how to use data to compete and deploying the right IT architecture and analytical capabilities. Past failures with CRM show that analytics initiatives need to align with companies' processes and decision-making.
Big data and analytics have become increasingly important in the corporate world. Venture capital investments in big data are growing exponentially. Research from MIT shows analytics can increase productivity by 5-6%. However, many companies are unsure how to implement analytics effectively. The document outlines three key capabilities for exploring big data: identify the right data sources, build advanced analytics models, and transform the organization to make better decisions based on data and models. Mastering these skills can help companies gain a competitive advantage.
The document discusses how cognitive computing and artificial intelligence are disrupting various industries by enabling non-traditional business models. It provides examples of the world's largest taxi, accommodation, retailer, and media companies that own no vehicles, real estate, inventory, or create content, respectively. The document advocates that companies leverage cognitive computing to gain insights from vast amounts of new data through predictive, descriptive, and cognitive capabilities. It outlines steps to become a cognitive business through developing a strategy, extending analytics with cognitive, moving to cognitive cloud services, building cognitive infrastructure, and adopting cognitive security.
This document discusses different perspectives on big data and outlines strategies for adopting and utilizing big data. It presents big data as trifurcated among plumbing/infrastructure, networks/security, and task development. It then outlines curves showing the evolution from spreadsheets to accelerated decision making as big data is accepted and utilized, with the goal of establishing an ecosystem where data strategy is separate from IT and knowledge workers are maximized.
The document discusses challenges with hiring data scientists and suggests alternative approaches. It recommends empowering small cross-functional data-oriented teams explicitly tasked with delivering measurable business benefits. This builds internal data capabilities rather than just hiring expertise. It also stresses the importance of making data science a cultural value throughout the organization so that all employees understand basic principles and practices of data science.
Data analytics for the mid-market: myth vs. realityDeloitte Canada
This document discusses 5 myths that prevent mid-market companies from making smarter decisions using data analytics. The myths are that they are not big enough to benefit, they just need more data, it is IT's responsibility, they are not equipped for it, and it won't provide new insights. The realities are that analytics levels the playing field, visualization tools make existing data more useful, analytics requires business leadership partnering with IT, starting small using cloud solutions is possible, and having a vision and strategy is key to realizing value from analytics.
Big Data Real Time Marketring Content Trends Chase McMichael
The document discusses how big data can provide real-time business intelligence. It notes that with real-time comes real-time problems where intelligence and adaptive data management is required. It also discusses three aspects of big data and how big data is changing business and IT, with mobile use and cloud computing driving big data growth. The document emphasizes that big data analysis requires a mix of data collection, organization, and insights to provide strategic and tactical intelligence for brands.
Big Data: Implications for Marketing and StrategyC.K. Kumar
This document discusses big data and its impact on strategy and marketing. It begins with definitions of big data and introduces some key principles. Some differences between big data and small data are outlined. The document then discusses the big data value chain and workflow. It provides examples of how Target and EGI have used big data successfully. Finally, it discusses how small and medium businesses can leverage big data and provides some key takeaways.
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
This webinar discussed the purpose of data analytics and how it can be a light in the darkness for your organization to make better decisions for the future. The webinar covered the purpose of data analysis and its definition, the fundamental steps to take to perform data analysis to problem solve, and closed with next steps that attendees can take to further develop data analysis and business intelligence within their organizations.
During this webinar, attendees learned about the following:
- How data analytics functions to help your organization improve.
- The process for using data analytics to solve problems.
- Next steps to take to build data analysis within your organization.
The document discusses business analytics and how it was used by the Cincinnati Zoo and Botanical Garden to increase revenue and attendance. Specifically, it allowed the zoo to optimize food outlet operations, eliminate underperforming products, and use visitor data to target marketing to increase attendance by 4.2%. In general, business analytics involves using data, analytics, and technology to help managers make better fact-based decisions to improve various business operations and outcomes.
Data-Analytics-Resource-updated for analysisBhavinGada5
Data analytics is the analysis of large volumes of data to draw insights. It is important for cost reduction, faster decision making, revenue growth, and risk management. There are four main types: descriptive analyzes what happened, diagnostic analyzes why it happened, predictive analyzes what will happen, and prescriptive recommends actions. Data analytics helps financial reporting and auditing through risk understanding, process improvements, and continuous monitoring. Businesses use analytics for insights to transform models and gain deeper customer insights. While investment in analytics is widespread, cultural challenges of people and processes are a larger barrier than technology.
Big data offers opportunities for companies to gain competitive advantages through improved customer intimacy, product innovation, and operations. The document discusses how various companies are leveraging big data across industries. It notes that 45% of companies have implemented big data initiatives in the past two years and over 90% of Fortune 500 companies will have initiatives underway soon. Harnessing big data's potential requires understanding where it can create value within a company and having the right organizational structure, technology investments, and plan to capture those benefits.
Big data offers companies a big advantage if they can harness enormous data sets that were previously impossible to process. The document discusses how big data is transforming business models through creative destruction, as more data is created every day from various sources. It provides examples of how companies in various industries like retail, banking, and manufacturing are using big data for customer intimacy, product innovation, and improving operations. Specifically, companies are able to better customize products and services, improve supply chain management, and gain real-time insights from vast amounts of structured and unstructured data.
Transforming Data into Insights, Decisions, and Actions ศาสตร์ของการใช้ตัวเลขและข้อมูล ใน Business Aspect เพื่อขับเคลื่อนองค์กรและกลยุทธ์ทางการตลาด with Case Studies
Is Your Company Braced Up for handling Big Datahimanshu13jun
Has your company recently launched new product or company is concerned with the poor sales figure or want to reach new prospects and also reduce the existing customers' attrition, then this thought evoking short hand guide is available for you to explore.
Module 2 - Improving current business with your own data - Online caniceconsulting
The document discusses how companies can improve their current business using their own internal data. It provides tips on locating internal data sources within a company, implementing data enrichment, and using data to build a company's brand. The key internal data sources discussed include transactional data, customer relationship management systems, internal documents/archives, and data from other business applications and device sensors. Data enrichment is presented as an important part of big data projects, to integrate and extract more value from existing data.
Organizations that are most likely to need big data management and analytical tools include:
- Government agencies - They collect and store vast amounts of data on citizens for public records, law enforcement, national security, etc.
- Large corporations - Companies in sectors like retail, banking, telecommunications generate huge volumes of customer data from transactions, web traffic, call records etc.
- Market research firms - They analyze big datasets to understand consumer behavior, market trends for their clients.
- Healthcare providers - Medical records, clinical research data is growing exponentially.
- Technology/Internet companies - Data is core to their business like search engines, social networks, e-commerce sites.
The common factor is that these organizations deal
Organizations that are most likely to need big data management and analytical tools include:
- Government agencies - They collect and store vast amounts of data on citizens for public records, law enforcement, national security, etc.
- Large corporations - Companies in sectors like retail, banking, telecommunications generate huge volumes of customer data from transactions, web traffic, call records etc.
- Market research firms - They analyze big datasets to understand consumer behavior, market trends for their clients.
- Healthcare providers - Medical records, clinical research data is growing exponentially.
- Technology/Internet companies - Data is core to their business like search engines, social networks, e-commerce sites.
The common factor is that these organizations deal
Organizations that are most likely to need big data management and analytical tools include:
- Government agencies that collect and store large amounts of data on citizens like national libraries, DMVs, tax authorities, etc. They need to efficiently manage and analyze this data.
- Security and law enforcement agencies that collect criminal records, complaints, public records etc. Analyzing these large datasets can help detect patterns and trends.
- Industries that generate massive amounts of operational data like utilities, telecom, transportation, retail etc. This data if analyzed can help optimize operations and improve customer experience.
- Market research and customer analytics companies that collect consumer surveys, website usage data etc. from many countries. Big data tools help analyze customer sentiment and
Organizations that are most likely to need big data management and analytical tools include:
- Government agencies - They collect and store vast amounts of data on citizens for public records, law enforcement, national security, etc.
- Large corporations - Companies in sectors like retail, banking, telecommunications generate huge volumes of customer data from transactions, web traffic, call records etc.
- Market research firms - They analyze big datasets to gain consumer insights for their clients.
- Healthcare providers - Medical records, clinical trials data, patient health metrics are growing exponentially.
- Technology/internet companies - Data is at the core of their business like social networks, ecommerce, cloud services etc.
The common factor is that these
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
The Evolving Role of the Data Architect – What Does It Mean for Your Career?DATAVERSITY
If you’re a data architect, you’ve heard it all—from ‘data management is the sexiest job of the 21st century’ to ‘data management is dead’. The truth almost certainly lies somewhere in the middle of the extremes, but how can you make sense of the true future of the data architect’s role in the rapidly-changing data landscape? The Data Architect holds a unique position as the translator between business value and technical implementation.
Join this webinar to learn how you can take advantage of the uniqueness of this role to catapult your career to the next level.
Age Friendly Economy - Improving your business with dataAgeFriendlyEconomy
The objective of this module is to gain an overview how you can use the data you already have available to improve your business.
Upon completion of this module you will:
- Learn the tips of how take advantage of the existing data you already have
- Be able to locate where internal data already lies within your company
- See how data can help you to build your brand
Big Data is Here for Financial Services White PaperExperian
Conquering Big Data Challenges
Financial institutions have invested in Big Data for many years, and new advances in technology infrastructure have opened the door for leveraging data in ways that can make an even greater impact on your business.
Learn how Big Data challenges are easier to overcome and how to find opportunities in your existing data and scale for the future.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
This whitepaper aims to assist Chief Data Officers in promoting a data-driven culture at their
organization, helping them lead the enterprise on a digital transformation journey backed by
analytical insights.
Neil Sholay - Data Driven Business - #OracleCloudDay LondonNeil Sholay
Information is replacing technology as the most critical business asset.
And so business leaders must make the data around and within their business ecosystem the centre of new planning, funding and revenue models.
This document discusses big data and the opportunities and challenges it presents for organizations. It notes that while big data has the potential to provide better insights, many companies lack the resources and processes to effectively leverage it. There is high demand for data analytics skills. Traditional data management approaches are insufficient for big data. The document outlines various big data use cases and solutions that Capstone can provide, including business analytics, data warehousing, self-service BI, data integration, infrastructure services, and strategic planning.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
2. Introduction
• Big data has been the most talked about emerging technology in recent times.
• However, for SMBs, the question is, does the cost and effort justify the value
to be derived from data?
• Big data analytics for small business provides deep insights that complement
human judgement.
• Forrester describes the power of big data for small business as “a major
disruption in the business intelligence and data management landscape.”
3. Success stories of benefiting Big Data for small business
1. Point defiance zoo & Aquarium Tacoma, Washington
• Unable to plan daily staffing commensurate with attendance.
• Major source of income was through attendance, which was highly dependent on
weather.
• By parsing historical data, and analysing it against decades of local weather data, they
found some predictable intelligence.
• This helped them to fine-tune their plans regarding staffing and promotional activities.
2. A lease-management company in North Carolina
• Manages nearly 1,000 rental properties in the outer banks,
• Unable to accurately predict profitability for homeowners through tourist rentals.
• Management found it impossible to analyse the data that they had amassed over the
years.
• The company opted for a business analytics tool, which distilled the data and simplified
the available information.
4. Big Data Solution
• Based on the data analytics, the company could share vital information with its
guests.
• They could now make rental-pricing recommendations to owners based on
seasonal trends and so forth.
• The business has grown by over 10 percent and costs reduced by 15 percent in the
last three years.
• Big data analytics for small business also helped this company to identify invoice-
processing errors, and overall it saved $50,000, annually.
5. Conclusion
What are you waiting for?
• Small and medium-sized businesses have a history of leading the change in
adopting emerging technologies.
• Big data for small business helps small organizations to watch and learn about their
customers and their preferences.
• For retaining customers and acquiring new ones, for up selling and cross-selling,
for streamlined processes, which lead to operational efficiency, big data has a hoard
of benefits that simply cannot be ignored!