The document discusses how companies do not need big data to make good decisions, but rather should empower employees to use smaller, more accessible data. It recommends that companies (1) delegate responsibilities to employees and trust them to make decisions using various data sources close to their work, (2) agree on a single source of truth for uniform data presentation, (3) use regular scorecards to provide performance feedback, (4) explicitly manage business rules to understand their impact, and (5) coach employees to shift from instinct to evidence-based decision making using the data available to them. This gradual cultural shift can spread effective data use throughout most roles in an organization.
Agile methods are becoming norm as the new working paradigm in our VUCA (volatile, uncertain, complex and ambiguous) world.
Organizations and teams are redesigning how they work in response to change or disruption in their market, as well as the need to gain competitive advantage through digital innovation or an enriched customer experience. The implications of Agile for Human Resources (HR) are huge and without shifting our existing HR processes, adoptability of agile become challenge.
It’s not about managing resources but rather managing people. Agile HR transforms the fundamental principles of HR to into People Operations leading Agile, digital and networked organizations. The aim is to build a shared value between your customers, business and people by:
Adopting a Mindset and a Culture – Embracing the Agile mindset within HR and people practices to incrementally deliver value to your customer
Co-create among the Organization – Applying Agile techniques, like Scrum and Kanban, to self-organize, experiment and co-create directly with your people.
Structure an organisation for connection, not control to empower people to give and do their best.
Agile methods are becoming norm as the new working paradigm in our VUCA (volatile, uncertain, complex and ambiguous) world.
Organizations and teams are redesigning how they work in response to change or disruption in their market, as well as the need to gain competitive advantage through digital innovation or an enriched customer experience. The implications of Agile for Human Resources (HR) are huge and without shifting our existing HR processes, adoptability of agile become challenge.
It’s not about managing resources but rather managing people. Agile HR transforms the fundamental principles of HR to into People Operations leading Agile, digital and networked organizations. The aim is to build a shared value between your customers, business and people by:
Adopting a Mindset and a Culture – Embracing the Agile mindset within HR and people practices to incrementally deliver value to your customer
Co-create among the Organization – Applying Agile techniques, like Scrum and Kanban, to self-organize, experiment and co-create directly with your people.
Structure an organisation for connection, not control to empower people to give and do their best.
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internship
How To Make The Most Out of Enterprise DataSnapShot
CHAT 2016 - China Hotel And Tourism Conference Presentation by Stefan Tweraser. SnapShot Hotel Analytics CEO Stefan Tweraser explains how business leaders can make the most out of the data available to them.
This is the analysis report of the HCS done as the part of the Data Analytics & Managerial relavance internship under the guidance of the Prof. Sameer Mathur(Ph.D,Carnige Mellon)IIM_LUCKNOW
Leaders Lab look into some key consultancy styles, establishing the framework for effective consultancy; building trust, communicating, listening and advising.
How to Make Your Organization a Problem Solving Machine With Toyota's 8 step ...Frank Donohue
Organizations don't plan to fail, they just don't have a structured system for problem solving. In this presentation you will find out how to solve problems the way one of the most successful, admired, studied, and emulated companies in the history of commerce solves problems and continuously improves its business and enjoys major breakthroughs time and time again.
How To Improve Profitability & Outperform Your Competition: the Guide to Data...A.J. Riedel
Find out how adopting data-driven decision-making can reduce your risk of making costly marketing and product mistakes and improve your product sell-through in this free E-Book.
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internship
How To Make The Most Out of Enterprise DataSnapShot
CHAT 2016 - China Hotel And Tourism Conference Presentation by Stefan Tweraser. SnapShot Hotel Analytics CEO Stefan Tweraser explains how business leaders can make the most out of the data available to them.
This is the analysis report of the HCS done as the part of the Data Analytics & Managerial relavance internship under the guidance of the Prof. Sameer Mathur(Ph.D,Carnige Mellon)IIM_LUCKNOW
Leaders Lab look into some key consultancy styles, establishing the framework for effective consultancy; building trust, communicating, listening and advising.
How to Make Your Organization a Problem Solving Machine With Toyota's 8 step ...Frank Donohue
Organizations don't plan to fail, they just don't have a structured system for problem solving. In this presentation you will find out how to solve problems the way one of the most successful, admired, studied, and emulated companies in the history of commerce solves problems and continuously improves its business and enjoys major breakthroughs time and time again.
How To Improve Profitability & Outperform Your Competition: the Guide to Data...A.J. Riedel
Find out how adopting data-driven decision-making can reduce your risk of making costly marketing and product mistakes and improve your product sell-through in this free E-Book.
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
Targeting towards the health and human services communities, this presentation covers the importance of a data-driven culture, how to identify areas where data can be used to innovate and how to recognize the operational processes you must have in place to fully utilize your data.
Stop the madness - Never doubt the quality of BI again using Data GovernanceMary Levins, PMP
Does this sound familiar? "Are you sure those numbers are right?" "Why are your numbers different than theirs?"
We've all heard it and had that gut wrenching feeling of doubt that comes with uncertainty around the quality of the numbers.
Stop the madness! Presented in Dunwoody on April 18 by industry leading expert Mary Levins who discusseses what it takes to successfully take control of your data using the Data Governance Framework. This framework is proven to improve the quality of your BI solutions.
Mary is the founder of Sierra Creek Consulting
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
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.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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
volume_up
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.
1. You may not need big data
after all
~ Jeanne W. Ross,
Cynthia M. Beath,
Anne Quaadgras
2. What’s the problem?
• Companies are not efficiently using Big data
for warehousing or for analyzing it.
• Turning insights from data analytics into
competitive advantage requires changes that
businesses may be incapable of making
• We are reluctant to make the change in our
organization that our insights might predict.
4. Delegate responsibilities
• There is a lot of little data.
• Employees should be aware of all the nuances
around them
• Solving all these small problems is much easier
than focusing on a very big problem using data
science.
6. One source
• Universal acceptance of one source of truth is
the first step in adopting a culture of
evidence-based decision making.
• Bet on the ability of good people to use good
data to make good decisions.
• When you have a pre-agreed set of numbers
presented in a uniform way, you can train the
company how to think about problems. It
gives you the context for making choices.
8. Performance Data
• Regular scorecards clarify individual
accountability and provide consistent feedback
so that individuals know how they are doing.
• It’s important for scorecards to be based on
the right metric.
• Perhaps the best way to teach people how to
use data to create business benefits is to
provide them with data about their own
performance.
10. • Little data can have a big effect on
performance when managers use the data
• Analyzing the impact of business rules doesn’t
involve the massive processing or the
statistical modeling associated with big data.
• Business Rules Are Running Your Company,
and You Don’t Even Know It
12. Training
• Training your employees every now and then.
• Only coaching your employees will update
them on your latest decisions.
• You have to help them shift from basing their
decisions on instinct to basing them on data.
• Just make them look at the data.
14. • In a culture of evidence-based decision
making, people who perform routine work
suddenly find themselves more responsible for
outcomes than for the number of hours they
put in
• Over time, the culture can spread to many,
maybe even most, roles.
• The opportunity presented by the information
economy is best tapped by getting all people
to use data more effectively