The last mile of the business analytics transformation--taking business analytics to the user--requires the alignment of goals, data, and models with business processes, technology and key performance indicators.
Four Key Considerations for your Big Data Analytics StrategyArcadia Data
Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).
Your smarter data analytics strategy - Social Media Strategies Summit (SMSS) ...Clark Boyd
The volume and velocity of available data brings with it a huge amount of new opportunities for marketers. However, without the analytics know-how to avail of this data, these are opportunities that are often missed. Moreover, the variety of different data sources and analytics platforms only add to this complexity.
This presentation covers:
- How to define and communicate an analytics framework
- How to set up analytics dashboards for a range of stakeholders
- The people and skills you need for an optimal analytics team
- Practical tips for improving your campaign measurement
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
Four Key Considerations for your Big Data Analytics StrategyArcadia Data
Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).
Your smarter data analytics strategy - Social Media Strategies Summit (SMSS) ...Clark Boyd
The volume and velocity of available data brings with it a huge amount of new opportunities for marketers. However, without the analytics know-how to avail of this data, these are opportunities that are often missed. Moreover, the variety of different data sources and analytics platforms only add to this complexity.
This presentation covers:
- How to define and communicate an analytics framework
- How to set up analytics dashboards for a range of stakeholders
- The people and skills you need for an optimal analytics team
- Practical tips for improving your campaign measurement
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
An introduction to analytics is a small presentation made for increasing awareness on analytics with some case studies of applying analytics in different functions.
These case studies are from informs.org which were openly available when the presentation was made. Due to confidentiality related obligations my personal experiences were shared - without naming clients - during the presentation. However, the case studies cannot be share on the PPT here. For more details or inputs on analytics you can reach me at twitter - @krdpravin or LinkedIn - https://in.linkedin.com/in/krdpravin
How to build a data analytics strategy in a digital worldCaseWare IDEA
This presentation will take you through TSB Bank’s journey from first establishing the audit function through to developing a data analytics strategy as the organization gets ready to move to a new, state-of-the-art online banking platform.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
How the analytics industry has been affected by descriptive, predictive and prescriptive techniques and how these traditional analytical techniques are going to transform the industry in future
Introduction to Business Analytics Part 1 published by BeamSync.
BeamSync is providing business analytics training course in Bangalore. If you are looking for analytics training then visit BeamSync. Regular classes are running during the weekend.
For details visit: http://beamsync.com/business-analytics-training-bangalore/
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
How Big Data and Predictive Analytics are Transforming the World of Accountin...Swenson Advisors, LLP
The age of the millennials is upon us: Google, Instagram, Snapchat, social media, competency based education (CBE) are changing the world we live in. Big Data, its “analytical off spring,” will significantly change the role and skill set of auditors and accountants in less than a decade.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
The Business Analytics Value PropositionEric Stephens
Presentation made to the Nashville Technology Council Analytics Peer Network meeting on May 30, 2013. Discussion of the impact of analytics to an organization, along with use cases that can help convey the value of the practice to executives and other managers.
Audit: Breaking Down Barriers to Increase the Use of Data AnalyticsCaseWare IDEA
Presenter: Lenny Block, Associate VP, Internal Audit, NASDAQ
While the majority of internal audit leaders and C-suite executives agree data analytics is important to strengthening audit coverage, only a small percentage of organizations are actively using data analytics regularly. Why is that? This webinar will explore challenges and barriers associated with starting, sustaining and expanding the use of data analytics to improve audit coverage.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics Staffing Models of Health Systems That Compete Well Using DataThotWave
Analytics Staffing Models of Health Systems That Compete Well Using Data
Analytic leaders are facing unprecedented pressure as expectations from the digitization of health drives questions from every corner of the enterprise. Along with the operational and workflow changes that come with digital health, we are seeing greater demand for data to support care transformation, risk contracting and organizational performance.
The time is right to consider how analytics can support organizational strategies and how we can ensure alignment across the organization. As part of the strategic alignment exercise we often see organizations consider how to best deliver advanced analytic capabilities and then ask themselves the question “how should we organize our analytic teams?” Often, an effective way to increase that efficiency, improve morale and achieve economy of scale is to consider changes to how analytics teams are organized.
The most appropriate organizational structure will vary based on the health system size, culture, and analytics (and data) maturity. Should the analytics capabilities be centralized, decentralized, or should we consider an alternative, hybrid staffing model? Should analytics sit under IT or medical leadership?
In our Data4Decisions talk, we will review the common models employed by leaders in healthcare, and describe how they align with business strategy. Further, we will outline common challenges as well as share success secrets via case studies from across the US healthcare landscape. The goal of this presentation is to provide the audience with a strong foundation for understanding the healthcare analytics staffing models used across the industry.
The demand for data insights to drive decisions is higher today than ever before. This isn't just because volumes of accessible data are growing, but also because people are more data literate and accustomed to engaging information experiences from consumer apps like LinkedIn, Google Maps, & Yelp.
This same thirst for intelligence is probably apparent in your user base, whether you realize it or not - and taking the time to invest in a data & analytics strategy for your product can yield significant customer & business benefits over time.
About the Speakers:
Michelle Bradbury,Director of Product Management, Pentaho
Michelle has over 18 years of experience in technology product & project management. She enjoys collaboratively creating & delivering highly compelling products and has held roles at organizations including Microsoft, Fujitsu, & CapitalOne. Michelle's areas of expertise include database and data warehouse architecture and development, project and budget management, as well as process definition and implementation for group cohesiveness.
Ben Hopkins, Product Marketing Manager, Pentaho
Ben is focused on embedded analytics & OEM partnerships. He has also held product marketing roles at Marketo and Salesforce.com. He holds an MBA from the U.C. Berkeley Haas School of Business as well as a BA in Economics from Harvard College.
Pentaho is delivering the future of analytics with a comprehensive platform for data integration & business intelligence. Learn more at www.pentaho.com.
Upcoming Events
Would you like to lead innovation efforts within your company? Attend upcoming product innovation courses. Visit: http://bit.ly/CILCourse
Looking for a coach to accelerate your product marketing & management career?
Set up a free initial 30-minute appointment for more information: http://bit.ly/1gBFdaD.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, contact AIPMM at certification@aipmm.com.
About AIPMM
The AIPMM is the trusted authority in product management. It is where product professionals go for answers. With members in over 75 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
Subscribe: http://www.aipmm.com/subscribe
Articles: http://www.aipmm.com/html/newsletter/article.ph
Membership: http://www.aipmm.com/join.php
An introduction to analytics is a small presentation made for increasing awareness on analytics with some case studies of applying analytics in different functions.
These case studies are from informs.org which were openly available when the presentation was made. Due to confidentiality related obligations my personal experiences were shared - without naming clients - during the presentation. However, the case studies cannot be share on the PPT here. For more details or inputs on analytics you can reach me at twitter - @krdpravin or LinkedIn - https://in.linkedin.com/in/krdpravin
How to build a data analytics strategy in a digital worldCaseWare IDEA
This presentation will take you through TSB Bank’s journey from first establishing the audit function through to developing a data analytics strategy as the organization gets ready to move to a new, state-of-the-art online banking platform.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
How the analytics industry has been affected by descriptive, predictive and prescriptive techniques and how these traditional analytical techniques are going to transform the industry in future
Introduction to Business Analytics Part 1 published by BeamSync.
BeamSync is providing business analytics training course in Bangalore. If you are looking for analytics training then visit BeamSync. Regular classes are running during the weekend.
For details visit: http://beamsync.com/business-analytics-training-bangalore/
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
How Big Data and Predictive Analytics are Transforming the World of Accountin...Swenson Advisors, LLP
The age of the millennials is upon us: Google, Instagram, Snapchat, social media, competency based education (CBE) are changing the world we live in. Big Data, its “analytical off spring,” will significantly change the role and skill set of auditors and accountants in less than a decade.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
The Business Analytics Value PropositionEric Stephens
Presentation made to the Nashville Technology Council Analytics Peer Network meeting on May 30, 2013. Discussion of the impact of analytics to an organization, along with use cases that can help convey the value of the practice to executives and other managers.
Audit: Breaking Down Barriers to Increase the Use of Data AnalyticsCaseWare IDEA
Presenter: Lenny Block, Associate VP, Internal Audit, NASDAQ
While the majority of internal audit leaders and C-suite executives agree data analytics is important to strengthening audit coverage, only a small percentage of organizations are actively using data analytics regularly. Why is that? This webinar will explore challenges and barriers associated with starting, sustaining and expanding the use of data analytics to improve audit coverage.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics Staffing Models of Health Systems That Compete Well Using DataThotWave
Analytics Staffing Models of Health Systems That Compete Well Using Data
Analytic leaders are facing unprecedented pressure as expectations from the digitization of health drives questions from every corner of the enterprise. Along with the operational and workflow changes that come with digital health, we are seeing greater demand for data to support care transformation, risk contracting and organizational performance.
The time is right to consider how analytics can support organizational strategies and how we can ensure alignment across the organization. As part of the strategic alignment exercise we often see organizations consider how to best deliver advanced analytic capabilities and then ask themselves the question “how should we organize our analytic teams?” Often, an effective way to increase that efficiency, improve morale and achieve economy of scale is to consider changes to how analytics teams are organized.
The most appropriate organizational structure will vary based on the health system size, culture, and analytics (and data) maturity. Should the analytics capabilities be centralized, decentralized, or should we consider an alternative, hybrid staffing model? Should analytics sit under IT or medical leadership?
In our Data4Decisions talk, we will review the common models employed by leaders in healthcare, and describe how they align with business strategy. Further, we will outline common challenges as well as share success secrets via case studies from across the US healthcare landscape. The goal of this presentation is to provide the audience with a strong foundation for understanding the healthcare analytics staffing models used across the industry.
The demand for data insights to drive decisions is higher today than ever before. This isn't just because volumes of accessible data are growing, but also because people are more data literate and accustomed to engaging information experiences from consumer apps like LinkedIn, Google Maps, & Yelp.
This same thirst for intelligence is probably apparent in your user base, whether you realize it or not - and taking the time to invest in a data & analytics strategy for your product can yield significant customer & business benefits over time.
About the Speakers:
Michelle Bradbury,Director of Product Management, Pentaho
Michelle has over 18 years of experience in technology product & project management. She enjoys collaboratively creating & delivering highly compelling products and has held roles at organizations including Microsoft, Fujitsu, & CapitalOne. Michelle's areas of expertise include database and data warehouse architecture and development, project and budget management, as well as process definition and implementation for group cohesiveness.
Ben Hopkins, Product Marketing Manager, Pentaho
Ben is focused on embedded analytics & OEM partnerships. He has also held product marketing roles at Marketo and Salesforce.com. He holds an MBA from the U.C. Berkeley Haas School of Business as well as a BA in Economics from Harvard College.
Pentaho is delivering the future of analytics with a comprehensive platform for data integration & business intelligence. Learn more at www.pentaho.com.
Upcoming Events
Would you like to lead innovation efforts within your company? Attend upcoming product innovation courses. Visit: http://bit.ly/CILCourse
Looking for a coach to accelerate your product marketing & management career?
Set up a free initial 30-minute appointment for more information: http://bit.ly/1gBFdaD.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, contact AIPMM at certification@aipmm.com.
About AIPMM
The AIPMM is the trusted authority in product management. It is where product professionals go for answers. With members in over 75 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
Subscribe: http://www.aipmm.com/subscribe
Articles: http://www.aipmm.com/html/newsletter/article.ph
Membership: http://www.aipmm.com/join.php
Gartner: The BI, Analytics and Performance Management FrameworkGartner
Further information on BI is available at www.gartner.com. Gartner will also host its Business Intelligence Summit 2011, 31 Jan- 1 Feb, London. More information at www.europe.gartner/bi.
BI Consultancy - Data, Analytics and StrategyShivam Dhawan
The presentation describes my views around the data we encounter in digital businesses like:
- Looking at common Data collection methodologies,
-What are the common issues within the decision support system and optimiztion lifecycle,
- Where are most of failing?
and most importantly, "How to connect the dots and move from Data to Strategy?"
I work with all facets of Web Analytics and Business Strategy and see the structures and governance models of various domains to establish and analyze the key performance indicators that allow you to have a 360º overview of online and offline multi-channel environment.
Apart from my experience with the leading analytic tools in the market like Google Analytics, Omniture and BI tools for Big Data, I am developing new solutions to solve complex digital / business problems.
As a resourceful consultant, I can connect with your team in any modality or in any form that meets your needs and solves any data/strategy problem.
Capturing Business Requirements For Scorecards, Dashboards And ReportsJulian Rains
This paper helps Management Information and Business Intelligence related projects build a solid foundation for their reporting business requirements gathering. It defines the scope of the information needed to design and build dashboards, scorecards and other types of report.
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.
07. Analytics & Reporting Requirements TemplateAlan D. Duncan
This document template defines an outline structure for the clear and unambiguous definition of analytics & reporting outputs (including standard reports, ad hoc queries, Business Intelligence, analytical models etc).
SM Energy and Akili Discuss How to Accelerate Your New Asset Assimilationrnaramore
Upstream Oil & Gas companies strategically look to acquire assets as a method for growth and market penetration. The integration of those new assets into their SAP environment is critical to gain the most value from the acquisition. Frequently the data conversion to an SAP system is considered a trivial task and is given inadequate attention in the overall integration timeline. A proper data conversion strategy is key to the success of supporting these assets within SAP. While working with SM Energy during their SAP ERP implementation, Akili developed a rapid deployment data migration solution to accelerate the conversion of critical data to support an acquisition.
Shows how RDS supports HANA, new Assemble to order Strategy utilizing RDS, Business Case studies tied to Technology and an evolution path for CRM utilizing RDS, HANA and the Cloud.
Operational Analytics Using Spark and NoSQL Data StoresDATAVERSITY
NoSQL data stores have emerged for scalable capture and real-time analysis of data. Apache Spark and Hadoop provide additional scalable analytics processing. This session looks at these technologies and how they can be used to support operational analytics to improve operational effectiveness. It also looks at an example of how operational analytics can be implemented in NoSQL environments using the Basho Data Platform with Apache Spark:
•The emergence of NoSQL, Hadoop and Apache Spark
•NoSQL Use Cases
•The need for operational analytics
•Types of operational analysis
•Key requirements for operational analytics
•Operational analytics using the Basho Data Platform with Apache Spark.
Dont make the SAP Hana story a difficult story is a true to life description of real life SAP Hana use cases that were able to be fixed and supported after making it easier to swallow.
How to Streamline Complex, Data-Intensive SAP Materials and Product Data Proc...Precisely
Drive success in 2022 with automation
More than ever, product success is reliant on complex, data-intensive processes to compete in today’s highly dynamic marketplace. Driving this complexity is an increasing reliance on SAP product data and the processes that create, manage, and use materials, customer, and vendor data.
In this on-demand webinar, we will discuss how Winshuttle (now a part of Precisely), the leader in data integrity, can help you:
- Automate manual SAP tasks to deliver quick results for mass data management challenges
- Automate complex, SAP-centric product data processes to help you get products to market faster while achieving higher data quality and better process governance
While there is a lot of buzz about advanced IT analytics (AIA), the global research from leading IT analyst firm Enterprise Management Associates (EMA) highlights what is actually going on, who is successful and why.
These slides - based on the webinar featuring Dennis Drogseth, VP of research at EMA - cover why successful AIA deployments leverage more 3rd party sources (the average is 15), support more roles (the average is 11), and why 96% of respondents want to integrate service interdependency data into their AIA solutions.
These slides cover:
**What are the more popular types of advanced IT analytics (AIA), and how are they being used?
**How have advanced IT analytics adoption patterns and priorities changed over the last 2 years?
**Who is driving AIA organizationally in the real world?
Nesta Apresentação a IT Mídia e a SAP vão ajudar a responder as seguintes questões:
O que é uma aplicação analítica?
Tendências e desafios
Por quê SAP?
As aplicações analíticas da SAP
Clientes SAP
Streamline Your Oil & Gas Master Data Processes Using PreciselyPrecisely
In today’s dynamic business environment, oil and gas companies rely on accurate and consistent master data to run efficiently. Unfortunately, with all of the disruptions, changes, and challenges facing the industry, the once reliable data management processes developed over the past few decades can no longer be relied on. Let us show you how, using Precisely’s Automate and EnterWorks platforms, you can improve the integrity of your master data in an ever-changing marketplace through automation, syndication, and standardization.
Enabling Better Clinical Operations through a Clinical Operations StoreSaama
Srini Anandakumar, Senior Director of Clinical Analytics Innovation for Saama, presented at the Big Data and Analytics in Pharma in Philadelphia, November 1, 2017.
#asksap Analytics Innovations Community Call - Take Action in 2017 with Innov...SAP Analytics
Learn more about the highly anticipated 2017 release of SAP BusinessObjects Lumira 2.0, the expanded modeling and scalable machine learning capabilities of SAP BusinessObjects Predictive Analytics 3.1, and the extended availability of SAP BusinessObjects Roambi.
These slides - based on the webinar - shed light on how business stakeholders make the most of information from their big data environments and the requirements those stakeholders have to turn big data into business impact.
Using recent big data end-user research from leading IT analyst firm Enterprise Management (EMA), data from Vertica’s recent benchmarks on SQL on Hadoop, and firsthand customer experiences, viewers will learn:
- Use cases where end users around the world are using big data in their organizations
- How maturity with big data strategies impact why and how business stakeholders use information from their big data environments
- How Vertica empowers the use of information from big data environments
Precisely Solutions For Manufacturing Supply ChainsPrecisely
Modern supply chains rely on accurate and consistent master data to run efficiently. Unfortunately, with all of the disruptions, changes, and challenges facing companies today, the once reliable supply chain management processes developed over the past few decades can no longer be relied on.
Let us show you how, using Precisely’s Automate and EnterWorks platforms, you can improve the integrity of your master data in a dynamic supply chain through automation, syndication, and standardization.
Similar to Enterprise Analytics Strategy: Taking Business Analytics to the User (20)
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Enterprise Analytics Strategy: Taking Business Analytics to the User
1. Enterprise Analytics Strategy:
Taking Business Analytics to the User
Ruben Mancha, PhD
Assistant Professor of Information Systems
Babson College
March 8, 2016
