Gartner had predicted that by 2020, 80% of organizations would initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. This has become even more critical to businesses today as they seek to adjust to the remote settings of the COVID-19 pandemic.
Advanced data literacy makes an organization faster, smarter, and better prepared to succeed in a data-driven environment. However, many organizations struggle to create a data-literate workforce.
In this webinar, Alissa Schneider, Sense Corp data governance leader, will examine the fundamentals of data literacy, why it’s important in today’s marketplace, and share the 10 steps you can take to enhance the data literacy in your organization.
Contact us for more information: https://sensecorp.com/business-consulting-contact/
Data Literacy and Data Virtualization: A Step-by-step Guide to Bolstering You...Denodo
Watch full webinar here: https://bit.ly/2KLc1dE
An organization’s effectiveness can only be as good as the understanding of their data. Hence it is important for both the frontline workers as well as the managers to be data literate, so that they can they understand how the business is functioning, decide if any changes need to be made, and quickly make decisions to realize better outcomes. However, successful data literacy requires stringent processes and an effective tool to operationalize them.
Listen to the our replay on the 10-steps to building a data-literate organization, and how data virtualization can help implement the underpinning processes.
Sense Corp and Denodo have partnered to combine state-of-the art professional services with the industry’s most advanced data virtualization platform to streamline data access in support of the most critical business needs.
Watch the replay to learn:
- The 10-steps to data literacy; what you can do to become a high performer.
- How to use data virtualization as the foundation to implementing data literacy processes.
- Examples of companies that have achieved high levels of data literacy.
Download the Sense Corp 10 Steps to Data Literacy eBook to learn more.
From Information Overload to Organized InsightsLexisNexis
As organizations navigate the ups
and downs of a complex global economy, access
to reliable, relevant information can help them
compete more effectively. To paraphrase Maya
Angelou, “When you know better, you do better.”
Information professionals play an important role
in identifying and disseminating the business
insights companies need to manage risk and
make smarter, faster decisions.
CDO Slides: A Chief Data Officer InterviewDATAVERSITY
Join John and Kelle as they talk to a Chief Data Officer (CDO). We will continue to explore why organizations hire CDO’s and how the CDO role is still evolving. We will examine some of the critical success factors and challenges of the role. This interview will also take a deeper dive into specific activities and value generated by the CDO positions.
In this webinar we will discuss:
•What were and are the biggest challenges?
•What kind of support do you get?
•What kind of business strategy planning are you a part of?
•What can be done differently?
8 Reasons to Stop Managing Your People with Spreadsheets (Higher Education)Cornerstone OnDemand
Everyone loves a good spreadsheet. But if you have more than a few hundred employees, it can be a nightmare to track performance, training and succession activities with real-time insight. Our clients share why they made the switch from spreadsheets to talent management software - check them out.
Data Literacy and Data Virtualization: A Step-by-step Guide to Bolstering You...Denodo
Watch full webinar here: https://bit.ly/2KLc1dE
An organization’s effectiveness can only be as good as the understanding of their data. Hence it is important for both the frontline workers as well as the managers to be data literate, so that they can they understand how the business is functioning, decide if any changes need to be made, and quickly make decisions to realize better outcomes. However, successful data literacy requires stringent processes and an effective tool to operationalize them.
Listen to the our replay on the 10-steps to building a data-literate organization, and how data virtualization can help implement the underpinning processes.
Sense Corp and Denodo have partnered to combine state-of-the art professional services with the industry’s most advanced data virtualization platform to streamline data access in support of the most critical business needs.
Watch the replay to learn:
- The 10-steps to data literacy; what you can do to become a high performer.
- How to use data virtualization as the foundation to implementing data literacy processes.
- Examples of companies that have achieved high levels of data literacy.
Download the Sense Corp 10 Steps to Data Literacy eBook to learn more.
From Information Overload to Organized InsightsLexisNexis
As organizations navigate the ups
and downs of a complex global economy, access
to reliable, relevant information can help them
compete more effectively. To paraphrase Maya
Angelou, “When you know better, you do better.”
Information professionals play an important role
in identifying and disseminating the business
insights companies need to manage risk and
make smarter, faster decisions.
CDO Slides: A Chief Data Officer InterviewDATAVERSITY
Join John and Kelle as they talk to a Chief Data Officer (CDO). We will continue to explore why organizations hire CDO’s and how the CDO role is still evolving. We will examine some of the critical success factors and challenges of the role. This interview will also take a deeper dive into specific activities and value generated by the CDO positions.
In this webinar we will discuss:
•What were and are the biggest challenges?
•What kind of support do you get?
•What kind of business strategy planning are you a part of?
•What can be done differently?
8 Reasons to Stop Managing Your People with Spreadsheets (Higher Education)Cornerstone OnDemand
Everyone loves a good spreadsheet. But if you have more than a few hundred employees, it can be a nightmare to track performance, training and succession activities with real-time insight. Our clients share why they made the switch from spreadsheets to talent management software - check them out.
Companies of all sizes are struggling to manage the massive amounts of data related to human resource management. This program will examine the various solutions technology offers to deal with this challenge, and provide examples to increase department efficiency while adding strategic value to the business. The following objectives will be covered during this presentation:
- Learn about the current and future trends in HR technology, including Employee Self Service, Business Intelligence, and Social Media.
- Discover how to harness technology to make strategic business decisions
- Learn how to turn data into knowledge through Key Performance Indicators, Dashboards, and other metrics.
- Learn how to develop a solid business case for HR technology.
UN Capacity Mapping 2020: Innovation, Data and Digital CapabilitiesKersten Jauer
The annual UN System Innovation, Data and Digital Capacity Assessment is designed to foster improvements in strategy, organizational design, culture, policy and practice across the UN family. Now in its third year, the assessment surveys leaders in UN System entities on the strength of organizational ‘capabilities’ and ‘cultures’. The main output is a ‘map’ that shows entities in four quadrants: Those organizations who are ‘leading’, those with ‘gaps in capability’ or ‘culture’, and those ‘at risk’ of falling behind.
Designed by the Secretary-General's Strategic Planning Unit with support from the UN Innovation Network, UNICEF, UNDP and the Chief Executive Board Secretariat, the 2020 edition measured 80 detailed change attributes and received inputs from leaders in over 50 UN System entities.
For decades, industries and companies around the world have known talent can serve as one of the best competitive advantages. It is also clear identifying the right talent for your business is vital because not everyone is going to be a perfect fit.
It’s been three years since the General Data Protection Regulation shook up how organizations manage data security and privacy, ushering in a new focus on Data Governance. But what is the state of Data Governance today?
How has it evolved? What’s its role now? Building on prior research, erwin by Quest and ESG have partnered on a new study about what’s driving the practice of Data Governance, program maturity and current challenges. It also examines the connections to data operations and data protection, which is interesting given the fact that improving data security is now the No. 1 driver of Data Governance, according to this year’s survey respondents.
So please join us for this webinar to learn about the:
Other primary drivers for enterprise Data Governance programs
Most common bottlenecks to program maturity and sustainability
Advantages of aligning Data Governance with the other data disciplines
In a post-COVID world, data has the power to be even more transformative, and 84% of business and technology professionals say it represents the best opportunity to develop a competitive advantage during the next 12 to 24 months. Let’s make sure your organization has the intelligence it needs about both data and data systems to empower stakeholders in the front and back office to do what they need to do.
Enterprise search, once a hot topic, now faces new challenges with the adoption of hybrid and cloud environments. In SharePoint and Office 365, search isn’t equal, and before jumping on the Office 365 band wagon, organizations need to know as much as they can about potential challenges and pitfalls. Even in a SharePoint stand-alone environment, the consumption of content is forcing a renewed look at security, information lifecycle management, and non-compliance. Join us on Tuesday, October 28th, at 11:30am – 12:30pm EDT for this webinar packed with information on how to address search issues in SharePoint stand-alone, Office 365 hybrid, or cloud-only environments.
If you’re not sure how you would answer any of the below questions below, then this webinar is for you:.
• Does an enterprise search engine that provides the same transparency both on-premise and in the cloud matter to you? Does it matter to your users?
• With the huge push for Office 365, is enterprise search getting lost?
• Will the announcement of Delve push you over the edge in adopting Office 365? Why?
• What about managing content in the cloud? Do you have any reservations about security,or records, and what your users are doing in the cloud? (Bet you’ll be surprised.)
• What about migration? What goes where?
• How will you know what’s on your users’ OneDrives? Is DLP enough?
• Is your SharePoint search good enough? Have you calculated the ROI you can gain by improving it?
• How are you going to manage the ever increasing consumption of organizational content?
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
data-literacy-the-key-to-unlocking-success-in-a-data-driven-world-2023-5-17-3...Data & Analytics Magazin
Are you still struggling to navigate through stacks of data sheets and pie charts? Fear not, my friend! It's time to up your data literacy game! In this day and age, you cannot afford to be data-challenged, unless you're going for the title of 'clueless bean counter '. Don't let data leave you flummoxed, bewildered, and feeling like a total ditz. The secret to unlocking success in this data-driven world is becoming data-literate. It's not rocket science - just a little elbow grease and a lot of Google searches. So, roll up your sleeves, put on your thinking cap, and embark on the journey of becoming a data ninja! Who knows, your newfound data superpowers may just land you that corner office you've been eyeing.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
Companies of all sizes are struggling to manage the massive amounts of data related to human resource management. This program will examine the various solutions technology offers to deal with this challenge, and provide examples to increase department efficiency while adding strategic value to the business. The following objectives will be covered during this presentation:
- Learn about the current and future trends in HR technology, including Employee Self Service, Business Intelligence, and Social Media.
- Discover how to harness technology to make strategic business decisions
- Learn how to turn data into knowledge through Key Performance Indicators, Dashboards, and other metrics.
- Learn how to develop a solid business case for HR technology.
UN Capacity Mapping 2020: Innovation, Data and Digital CapabilitiesKersten Jauer
The annual UN System Innovation, Data and Digital Capacity Assessment is designed to foster improvements in strategy, organizational design, culture, policy and practice across the UN family. Now in its third year, the assessment surveys leaders in UN System entities on the strength of organizational ‘capabilities’ and ‘cultures’. The main output is a ‘map’ that shows entities in four quadrants: Those organizations who are ‘leading’, those with ‘gaps in capability’ or ‘culture’, and those ‘at risk’ of falling behind.
Designed by the Secretary-General's Strategic Planning Unit with support from the UN Innovation Network, UNICEF, UNDP and the Chief Executive Board Secretariat, the 2020 edition measured 80 detailed change attributes and received inputs from leaders in over 50 UN System entities.
For decades, industries and companies around the world have known talent can serve as one of the best competitive advantages. It is also clear identifying the right talent for your business is vital because not everyone is going to be a perfect fit.
It’s been three years since the General Data Protection Regulation shook up how organizations manage data security and privacy, ushering in a new focus on Data Governance. But what is the state of Data Governance today?
How has it evolved? What’s its role now? Building on prior research, erwin by Quest and ESG have partnered on a new study about what’s driving the practice of Data Governance, program maturity and current challenges. It also examines the connections to data operations and data protection, which is interesting given the fact that improving data security is now the No. 1 driver of Data Governance, according to this year’s survey respondents.
So please join us for this webinar to learn about the:
Other primary drivers for enterprise Data Governance programs
Most common bottlenecks to program maturity and sustainability
Advantages of aligning Data Governance with the other data disciplines
In a post-COVID world, data has the power to be even more transformative, and 84% of business and technology professionals say it represents the best opportunity to develop a competitive advantage during the next 12 to 24 months. Let’s make sure your organization has the intelligence it needs about both data and data systems to empower stakeholders in the front and back office to do what they need to do.
Enterprise search, once a hot topic, now faces new challenges with the adoption of hybrid and cloud environments. In SharePoint and Office 365, search isn’t equal, and before jumping on the Office 365 band wagon, organizations need to know as much as they can about potential challenges and pitfalls. Even in a SharePoint stand-alone environment, the consumption of content is forcing a renewed look at security, information lifecycle management, and non-compliance. Join us on Tuesday, October 28th, at 11:30am – 12:30pm EDT for this webinar packed with information on how to address search issues in SharePoint stand-alone, Office 365 hybrid, or cloud-only environments.
If you’re not sure how you would answer any of the below questions below, then this webinar is for you:.
• Does an enterprise search engine that provides the same transparency both on-premise and in the cloud matter to you? Does it matter to your users?
• With the huge push for Office 365, is enterprise search getting lost?
• Will the announcement of Delve push you over the edge in adopting Office 365? Why?
• What about managing content in the cloud? Do you have any reservations about security,or records, and what your users are doing in the cloud? (Bet you’ll be surprised.)
• What about migration? What goes where?
• How will you know what’s on your users’ OneDrives? Is DLP enough?
• Is your SharePoint search good enough? Have you calculated the ROI you can gain by improving it?
• How are you going to manage the ever increasing consumption of organizational content?
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
data-literacy-the-key-to-unlocking-success-in-a-data-driven-world-2023-5-17-3...Data & Analytics Magazin
Are you still struggling to navigate through stacks of data sheets and pie charts? Fear not, my friend! It's time to up your data literacy game! In this day and age, you cannot afford to be data-challenged, unless you're going for the title of 'clueless bean counter '. Don't let data leave you flummoxed, bewildered, and feeling like a total ditz. The secret to unlocking success in this data-driven world is becoming data-literate. It's not rocket science - just a little elbow grease and a lot of Google searches. So, roll up your sleeves, put on your thinking cap, and embark on the journey of becoming a data ninja! Who knows, your newfound data superpowers may just land you that corner office you've been eyeing.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
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.
Data Driven Culture with Slalom's Director of AnalyticsPromotable
Everyone wants to capture the benefits of big data by making better data driven decision. We are inundated by analytical tools that deliver "insights" and process information quickly.
Although often overlooked, creating a data driven culture is as important as finding the right tools to make data driven decisions. Organizations who skip this foundational element often find their investment in Data tools and personal don't yield the benefits that becoming Data Driven is supposed to unlock.
In this talk you'll learn about why creating a Data Driven culture is vital to every organization and the starting point for ensuring your data strategy generates strong impact and ROI.
Takeaways:
What is a data driven culture? Where does it start?
What happens when you implement tools (tableau, power BI, Machine Learning, etc) without first having a data driven culture
Stages of a Data Driven Culture?
How to get started?
Your Instructor: Kevin Chapin is the Practice Director for Data and Analytics at Slalom Consulting.
To see the full talk, click here: https://www.youtube.com/watch?v=7xNLgiK31Is
Data Governance, the foundation for building a succesful data managementTentive Solutions
This Whitepaper clearly explains how the Data Governance function plays a key role and which factors are of great importance in successful data management. Also available in Dutch.
In this new paper, I explore the organisational and cultural challenges of implementing information governance and data quality. I identify potential problems with the traditional centralised methods of data quality management, and offer alternative organistional models which can enable a more distributed and democratised approach to improving your organisations data. I also propose a simple four-step approach to delivering immediate business value from your data.
Driving A Data-Centric Culture: The Leadership ChallengePlatfora
Embracing data as a corporate asset—and a source of competitive advantage—is not just a “good idea” that companies should consider. Such adoption will help determine the winners and losers across multiple markets and industries in the future.
In the last couple of years, corporate focus has shifted: first, from investing in the right technology and tools; then to acquiring the right talent and skills; and now to building the right organizational culture that can realize the business value of powerful big-data analytic tools.
Most organizations today are still focused on putting in place the right technology and talent, but others have evolved further and are working toward fostering a data-centric corporate culture.
How organizations can become data-driven: three main rulesAndrea Gigli
The presentation shows how organization can successfully become data driven and avoid wasting time and money. It explain how to prioritize business questtions, how to combine properly people, tech&data and processes, and how to structure a transforamtional journey for becoming a data driven.
Big data & data science challenges and opportunitiesJose Quesada
Even when most companies see the advantages of using more data in their decisions, few actually do. Why is that? A few ideas on challenges and opportunities for (middle-size) companies. Talk audience was an engineering association, where most people represented engineering-centric companies in Germany (often in manufacturing).
Building an Effective Data Management StrategyHarley Capewell
In June 2013, Experian hosted a Data
Management Summit in London, with over
100 delegates from the public, private and
third sectors. Speakers from Experian
and across the data industry explored the
challenges of developing and implementing
data quality strategies - and how to
overcome them. Read on for more information.
Driving A Data-Centric Culture: A Bottom Up OpportunityPlatfora
Big data has captured the attention of business leaders in almost every industry. Building big-data capabilities has found its place on the corporate agenda, and leading companies are moving forward on promoting a data-centric culture.
Most data-driven companies are focused on the leadership challenge of inspiring this cultural shift. To date, however, little has been said about the role of middle management and lower-level employees in spreading and institutionalizing a data-centric culture.
The Future of the Digital Experience: How to Embrace the New Order of Busines...Sense Corp
If we learned anything in 2020, it’s that we need to be able to adapt. COVID-19 accelerated what was already a rapid pace of change. Every industry has been disrupted, and the digital experience is more important than ever. It is crucial to move from a digital tracked customer, to a digital engaged model, and finally, to a digital reimagined future.
In this webinar, our Transformation practice lead Michael Daehne, will share a view into the future of business and how to get ahead of the change. He will walk through 7 considerations to make sure you embrace the new order of business in your industry.
1. Create Your Digital Transformation Roadmap
2. Strive to be a Data Leader – Not a Tech Leader
3. Adopt an Agile Mindset
4. Unbundle and Re-bundle the Value Chain
5. Explore the Power of the Platform
6. Integrate Location and Event Independence
7. Implement Personalization at the Core of Every Service
Achieve New Heights with Modern AnalyticsSense Corp
Businesses can leverage modern cloud platforms and practices for net-new solutions and to enhance existing capabilities, resulting in an upgrade in quality, increased speed-to-market, global deployment capability at scale, and improved cost transparency.
In this webinar, Josh Rachner, data practice lead at Sense Corp, will help prepare you for your analytics transformation and explore how to make the most on new platforms by:
Building a strong understanding of the rise, value, and direction of cloud analytics
Exploring the difference between modern and legacy systems, the Big Three technologies, and different implementation scenarios
Sharing the nine things you need to know as you reach for the clouds
You’ll leave with our pre-flight checklist to ensure your organization will achieve new heights.
AI can give your organization the competitive advantage it needs, but the alarming truth is that only 1 in 10 data science projects ever make it into production. To be successful, organizations must not only correctly design and implement data science, but also raise the data, numerical, and technology literacy across the business.
Attend this webinar to learn what common pitfalls you need to avoid to keep your data science projects from failing. Data Scientist Gaby Lio will engage with the audience about project dos and don’ts to ensure your project success. She will then walk through three client use cases to give examples of successful data projects at each stage in the journey to AI adoption.
Small Investments, Big Returns: Three Successful Data Science Use CasesSense Corp
No journey is alike, and neither is the timeline of climbing towards full AI adoption. With varying ranges of technical capability and business readiness, one thing is for certain, you need to see results, and fast! In this webinar, we will explore three client use cases from the manufacturing industry, to oil and gas, to education with examples of successful projects including:
Sales Forecasting – We will share sales forecasting and market segmentation techniques in the manufacturing industry. Using historical sales data, we introduce fast and effective signal decomposition and clustering techniques to produce valuable customer insights.
Inventory Management – We apply text analytics and natural language processing techniques for advanced and custom automation. This use case saves significant time for inventory managers and analysts by accurately and rapidly classifying their inventory based on each item description.
Public Safety – We introduce a computer vision capability that can recognize firearms and trigger alerts. In this use case, we apply real-time object recognition technology for early detection of firearms for school safety.
You’ll walk away with modern analytics and AI tools to benefit your organization’s immediate needs no matter where you are on your journey to AI adoption.
AI can give your organization the competitive advantage it needs, but the alarming truth is that only 1 in 10 data science projects ever make it into production. To be successful, organizations must not only correctly design and implement data science, but also raise the data, numerical, and technology literacy across the business.
Attend this webinar to learn what common pitfalls you need to avoid to keep your data science projects from failing. Then Data Scientist Gaby Lio will engage with the audience about project dos and don’ts and leave you with a checklist to ensure your projects success.
Managing Large Amounts of Data with SalesforceSense Corp
Critical "design skew" problems and solutions - Engaging Big Objects, MuleSoft, Snowflake and Tableau at the right time
Salesforce’s ability to handle large workloads and participate in high-consumption, mobile-application-powering technologies continues to evolve. Pub/sub-models and the investment in adjacent properties like Snowflake, Kafka, and MuleSoft, has broadened the development scope of Salesforce. Solutions now range from internal and in-platform applications to fueling world-scale mobile applications and integrations. Unfortunately, guidance on the extended capabilities is not well understood or documented. Knowing when to move your solution to a higher-order is an important Architect skill.
In this webinar, Paul McCollum, UXMC and Technical Architect at Sense Corp, will present an overview of data and architecture considerations. You’ll learn to identify reasons and guidelines for updating your solutions to larger-scale, modern reference infrastructures, and when to introduce products like Big Objects, Kafka, MuleSoft, and Snowflake.
Have you heard the hype that the Data Warehouse is dead?
With technologies like the Data Lake and emerging data visualization tools continuing to evolve in the data space, enthusiasts are questioning whether conventional data layers like the data warehouse are still required to support your enterprise data strategy. While it may seem practical to move away from a data warehouse, it won’t be long before you start realizing the pitfalls of that approach. Like it or not, the data warehouse will continue to play an integral role in your organization’s Enterprise Information Architecture by ensuring actionable insights are being delivered with clean certified data.
In this session, Kunal Sharma, senior enterprise architect at Sense Corp, will:
Highlight the value of establishing a Clean Data Practice through governed data assets
Make a distinction between what “Single Source of Data” and “Best Version of The Truth” mean for an organization
Share uses cases for delivering certified data through a data warehouse
Provide a conceptual viewpoint of Enterprise Data Architecture design
Share an example of a modern analytics infrastructure platform
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.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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.
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
1. 10 Steps to Develop a Data
Literate Workforce
1
2. 2
Data Governance Practice Leader
Dallas / Fort Worth
aschneider@sensecorp.com
Alissa Schneider
About the Presenter
15+ years leading complex data
transformation projects for Fortune
500 and mid-size companies
3. 3
• What is Data Literacy?
• Why is Data Literacy Important?
• Audience Survey
• 10 Steps to Develop and Foster a Data
Literate Workforce
• Q & A
AGENDA
4. 4
Data-literate companies that are successfully
navigating this gap are already disrupting
industries, fundamentally changing expectations
and service levels.
What is Data Literacy?
Data literacy is the ability to read, work with, analyze, and argue
with data. Much like literacy as a general concept, data literacy
focuses on the competencies involved in working with data.
5. Learning to speak data? Here is what we learn at each step:
5
Reading Data
The organization has a limited amount of data
literacy established across the enterprise. It
may exist in certain departments but not
across the organization. The organization has
made limited investments in data literacy.
o Understanding Data Literacy Building Blocks
o Developing a Foundation of Data
o Questioning the Quality of Data
Writing Data
The organization is working to establish and
educate the organization on data literacy.
Education is a priority for every employee,
from data-focused departments to front-line
employees. The organization is actively
investing in data literacy and hiring
accordingly.
o Conducting Data Analysis
o Presenting with Data
o Telling the Story with Data
Speaking Data
The organization is data-literate and has
prioritized its data as a core asset. All
employees recognize the value of data. The
organization is investing to further the reach
of data literacy with leading-edge technologies
(e.g. AI/ML).
o Evaluating Data Ethics
o Making Decisions with Data
o Tracking Progress with Data
1 32
6. Data Literacy and COVID-19
6
Sources:
• https://www.theatlantic.com/health/archive/2020/05/cdc-and-states-are-misreporting-covid-19-test-data-pennsylvania-
georgia-texas/611935/
• https://www.nytimes.com/2020/05/22/us/politics/coronavirus-tests-cdc.html
• https://www.npr.org/sections/coronavirus-live-updates/2020/05/21/860480756/scientists-warn-cdc-testing-data-could-
create-misleading-picture-of-pandemic
7. Human Progress and Literacy
7
Throughout history, the literate people of their time have always led.
Literacy is the road to human progress and the means through which every man,
woman, and child can realize his or her full potential.
8. Key Findings
8
Enterprise-wide data literacy is low.
24% of business decision makers surveyed
are fully confident in their ability to read,
work with, analyze, and argue with data.
Future employees are underprepared for
data-driven workplaces.
21% of 16- to 24-year-olds are data-literate,
suggesting schools and universities are failing
to ensure students have the skills they need to
enter the working world.
Data is key for professional credibility.
94% of respondents using data in their
current roles agree data helps them do their
jobs better, and 82% believe greater data
literacy would give them more credibility in
the workplace.
Senior leaders do not display confidence.
32% of the C-suite is viewed as data-literate,
potentially holding senior leaders back from
encouraging their workforces to use data to
their advantage.
Organizations are losing competitive
advantage because data literacy drives
higher enterprise performance.
85% of data-literate people say they are
performing very well at work, compared
to 54% of the wider workforce.
There is an appetite to learn.
78% of business decision makers said they
would be willing to invest more time and
energy into improving their data skillsets.
Source: Lead with Data: How to Drive Data Literacy in the Enterprise, Qlik
9. Companies that use data to establish their business models
have 3 distinct advantages over established companies:
9
High-Quality Data Collection
Each process and interaction is evaluated
through a “can-I-track-this” lens followed by a
“how-can-I-scale-this” discussion. This
requires a strong foundation of underlying
data to be captured at every step.
Established companies often have legacy
processes with limited and disparate data
collection from which the data might be of
questionable quality.
Strong Data-literate Workforce
Knowing how to work with data is the
“minimum height to ride” at a data-literate
company. These companies hire strong data
practitioners who, through an increasing focus
on data, have been able to monetize their data
assets.
Established companies need employees who
can maintain their existing non-data based
processes, so they hire differently. Developing
data literacy is typically not a priority for them
and is reflected in their workforce.
Agility as a Mindset
The culture at these companies is focused on
their abilities to bring products to market
quickly, move critical decision making to front-
line managers, promote innovative thinking,
foster competitive drive, and rapidly evaluate
progress based on data.
Established companies work hard to adopt
these traits on small teams but struggle to
scale them throughout the organization,
where employees prefer to operate as-is.
10. The data practices that differentiated high performers from
others involved data leadership in the C-suite, broadly
accessible data, and a culture that tolerates failure.
1. Out of 10 practices that were presented as answer choices. For respondents at high-performing organizations, n = 170; for all other respondents, n = 405.
2. Respondents who said their organizations (a) have had an average annual organic growth rate of 10% or more over past 3 years and (b) have had an
average annual growth rate in earnings before interest and taxes of 10% or more over past 3 years.
Current data practices at respondents’ organizations1
% of respondents
At all other
organizations
At high-performing
organizations2
C-Suite team includes
at least one data leader
Data are broadly accessible
to front-line employees
whenever needed
Organizational culture
supports rapid testing and
iteration based on data and
tolerates fast failure
Hiring criteria for non-
management roles include
proficiency in data-related
topics
Hiring criteria for
management roles include
proficiency in data-related
topics
Catch Them if You Can: How Leaders in
Data and Analytics Have Pulled Ahead,
McKinsey & Company; Survey
11. Established companies often feel like
prisoners to what made them
successful – their static processes and
hierarchical controls.
Meanwhile, the new kids in class are
faster, smarter, and better prepared to
succeed in a data-driven environment.
13. 13
1. Have you ever heard anyone at your organization talk
about or discuss the need for Data Literacy?
orYES NO
14. 14
2. In terms of maturity, on a 1-5 scale, how would you
rank your organization’s enterprise-wide data literacy?
CHAOTIC
AD-HOC & UNKNOWN
REACTIVE
UNPREDICTABLE & REACTIVE
DEFINED
PROACTIVE, RATHER THAN REACTIVE
INTEGRATED
MEASURED & CONTROLLED
OPTIMIZED
STABLE & FLEXIBLE
15. 15
Assess Data Literacy Status
01
Develop a Data Literacy Strategy
02
Secure Executive Support
03
Identify Data Champions
04
Invest in a Data Literacy Foundation
05
Develop a Customized Data Literacy Curriculum
06
Use Data in Decision Making
07
Provide Access to Data
08
Hire Data Savvy Employees
09
Integrate Data into Daily Activities
10
The 10 Steps to Fostering a
Data-Literate Workforce
16. 01Data Pride Data Platform Data Prowess
This refers to how much the organization
recognizes and values data. We can determine
this by asking the following questions:
o Does your organization inherently
value data?
o What is the organization’s sentiment
about data?
o Does your entire organization value
data as an asset?
o Is every process and interaction viewed
as a source of valuable data?
o Does the organization push for
automated data collection where possible?
o Do front-line workers recognize the
value of collecting high-quality data?
This refers to how much of the organization’s
data is easily accessible in a highly useable
format. We can determine this by asking the
following questions:
o Does your organization make its data
easily available in a high-quality format?
o Are business and technology working
together to open up the data?
o Does the organization host the data in an
easy-to-access manner?
o Does the organization invest in breaking
down data silos?
o Does the organization certify a set of the
overall data across the enterprise?
o Does the organization invest in data
standards?
o Does the organization offer a set of
enterprise tools to provide the data to
employees?
o Does the organization invest in
collaborative uses of data?
This refers to how much the organization
knows about working effectively with
data. We can determine this by asking the
following questions:
o Does your organization understand and
know how to work with data?
o Are the organization’s employees data
savvy?
o Does the organization know how to convert
business questions into data questions?
o Does the organization understand how to
interpret and analyze data?
o Does the organization understand how to
communicate with data?
o Is the organization using artificial
intelligence, machine learning, and data
science?
Assess Data Literacy Status
17. DataProwessDataPlatformDataPride
High PerformersMid PerformersLow Performers
A few departments value data, but by and large, the
organization operates with the inertia of its
established processes and organizational structure.
There is a limited effort across the organization to
capture or create high-quality, automated, and
standardized data. Collection of data feels
burdensome because there is limited to no direct
value attached to it. Front-line workers don’t quite
understand why existing processes require certain
data to be captured.
A number of departments value data in the
organization and are beginning to see the value of
data as an asset that can drive competitive
advantage. There are pockets of initiatives to
capture and create high-quality, automated, and
standardized data. Collection of high-quality data,
while still challenging, is desired. Front line workers
understand the importance of capturing operational
data in a timely manner but need improved
processes and systems.
Most departments across the organization see value
in collecting every aspect of data and are using data
competitively. The organization is actively investing
in capturing high-quality data and leveraging
automated processes. Collection of data is
widespread and actively managed and coordinated.
Front-line workers clearly understand both the value
and need for quality and timely data and have
efficient processes and systems that aid in the
capture of data.
Most of the organization data is locked up in
legacy or functional systems with access through
reporting technologies. Some form of an enterprise
data warehouse might exist but with only a limited
set of enterprise data collected and integrated.
Data standards are lax and limited to certain system
implementations. Reporting and analytical
technologies are not broadly available or deployed
across the organization.
Some of the organization data is still locked up in
legacy or functional systems but there is a
substantial effort underway to unlock this data. An
enterprise data warehouse exists and there is a
concerted effort involving business and IT to
provide certified data. Establishing data standards is
still a work in progress but gaining momentum.
Reporting and analytical technologies are broadly
available across the organization, but adoption is
still underway.
Most of the organization’s data has been
integrated and made available through internal
and external data platforms. The organization is
also actively investing in data lakes and other newer
data platform technologies. Certified data is widely
available. Business and IT organizations actively
manage data standards and data usage. Reporting
and analytical technologies have been deployed
and are in use across the organization.
Decisions are based on anecdotal assessments and
are highly instinct-driven. There is a limited effort
undertaken to evaluate underlying data to assist
with a decision. Data used to make decisions is
often communicated by simply displaying the data.
Not much is done to weave the data into a story.
The organization has made limited investments in
advanced analytics capabilities.
Decisions are starting to be based on underlying
data, and decision-makers ask questions about the
data and its source and validity. The data used to
make decisions is displayed using data visualization
to enhance storytelling and gain buy-in. The
organization is making tangible and focused
investments in advanced analytics capabilities such
as machine learning.
Decisions are mainly insight-driven and utilize a
strong foundation of data. The decision-makers
converse fluently using data terms. There is active
use of data visualization to communicate business
decisions. Business and data weave
interchangeably. The organization is using advanced
analytic capabilities to drive their competitive
advantage.
18. 18
02Develop a Data Literacy Strategy
Distinguish where you are from where you want to be
Set the “baseline” from your assessment, identify your goals,
and incorporate continuous improvement after that.
01
02
03
04
05
Create an actionable plan for how to get there
Include all necessary tasks, develop interim steps, identify
dependencies and roadblocks, and customize for your
organization.
Align around the strategic value of data and the role data
literacy plays
This is where the organization must buy into a cultural shift
and recognize what it means to be a data-driven company.
Gather the necessary resources
Strategy success depends on ensuring you have the right
resources with the right skills, empowered in the right way
with the right enterprise reach. Remember, data literacy is not
an IT driven project – that’s the wrong mindset.
Ensure the plan is achievable and executable
Review goals and tactics, take a leadership approach to make
things happens, be a proponent of change, and above all –
do data dailySM.
Once you have completed your data
literacy assessment and understand your
company’s data literacy status, you can
begin to develop a comprehensive data
literacy strategy.
Each strategy will be unique to a
company’s data literacy status and needs,
but the process for development is similar
and typically requires the following
actions:
19. 19
03
The Beauty of
Data Visualization
The Best Stats
You’ve Ever Seen
Why Everyone
Should Be Data
Literate
The Power in
Effective Data
Storytelling
Executives can inspire their organizations to lean into
the world of data by sharing stories such as the ones
provided in these TED talks:
Secure Executive Support
20. 20
04Identify Data Champions
WHOARE
THEY?
Confident Data-Fluent
Communicators
Serving in Any Area of the
Business
Ask Challenging Questions
Desire Data-Driven
Answers
Seek Out Answers, Join
Forums, Encourage Sharing
WHO ARE YOUR DATA CHAMPIONS?
21. 05Invest in a Data Literacy Foundation
Educate the organization on data elements
and data use
01
02
03
04
05
Emphasize the importance of reading, writing,
and speaking data in a business setting
Allow employees to practice with data
through data apprenticeships
Create data certification milestones
Communicate the availability of enterprise
data assets
If you aren’t sure where to start, reference The
Data Literacy Project. This site is supported by
data analytics leader Qlik and features courses
that cover data fundamentals, foundational
analytics, data-informed decision making, and
advanced analytics.
Building a foundation of data literacy in an
organization requires an investment not
only in technology, but in education as
well. Employees should be trained to
understand data concepts, work with data,
and make accurate decisions based on
data.
To build your data literacy foundation, you
should consider setting up a Data
University or similar function within the
enterprise data organization that will:
22. o Build and practice the data literacy concepts. Discuss different types of data,
how to differentiate them, and how to “speak” data in a business setting.
o Make the curriculum a mix of theoretical concept and practical application.
Challenge students to apply what they learn to their daily activities.
o Make it interesting. Incorporate games for competition or integrate storytelling
activities to discuss how people used data to drive business differently.
o Create a tailored experience. Customize the material for different audiences,
their roles, their learning styles, their needs, and the tools they use.
o Develop a mentoring program. Start a “buddy system” to help those who might
be struggling with data concepts.
o Tie coursework into career paths, performance reviews, and incentive structures.
This will ensure more widespread participation across the organization.
06Develop a Customized Data Literacy Curriculum
23. 07Use Data in Decision Making
Convert the business decision to a data question
Evaluate how to bring insights rather than instinct to the business
decision. Evaluate data points that would help inform the decision one
way or the other.
01
02
03
04
05
Collect the data from trusted sources
Identify the underlying data that will be needed and obtain the data
from trusted data sources. That means two things: understanding
the context of the source data and assessing the quality of the data.
Consider the analysis options available
Evaluate the options for how to work with this data, what analytic
techniques and models might be available for use, and how to conduct
the needed analysis. Peel back the layers as you approach the problem
from different angles to prove or disprove your decision. Leverage
defined Key Performance Indicators (KPIs) where available.
Communicate the decision clearly
Utilize storytelling with data techniques to communicate your decision.
Recognize that stakeholders might need varying levels of
communication. Be clear about your deliberation and decision.
Conduct retrospective reviews
Collect new data points and as time goes by to evaluate your decision.
Recognize that no decision is bulletproof and in hindsight certain
decisions might have been made differently. Learn and adjust.
Organizations should think of business
problems in data terms: collect the
required data from trusted sources,
understand how to analyze data, learn how
to communicate the decision based on the
data, and analyze new data to evaluate the
decision.
To do this, organizations should leverage
the following framework to increase
critical thinking and move decision-making
from instinct-driven to insight-driven.
24. 24
08
Big data governance requires special attention, as this
data may move from one setting to another. A
portion of this data might be used in a laboratory
before moving to a factory. The data will need
definitions and a defined process as it moves to the
factory setting and is used for production.
Provide Access to Data
25. o They include metrics to highlight their accomplishments on their resumes.
o They can explain how to convert business questions to data questions.
o They can talk about and demonstrate their data handling skills.
o They can describe the use of Key Performance Indicators (KPIs).
o They can describe data problems they have solved.
o They can describe challenges that typically exist with dirty data.
09Hire Data Savvy Employees
Here are a few ways for an HR department to identify
data-savvy recruits:
26. 26
Meetings
Set the tone at the start of the meeting by walking through an
agenda and explaining the goal of the meeting. During the
meeting, remind everyone to leverage data-based decision
making where possible. When closing the meeting, check if
the goals were accomplished. By doing this daily across the
organization, the culture will begin to shift.
01
02
03
Company Communications
As the organization highlights insights based on data in regular
company communications, the role and prominence of data
increases. The organization can leverage data-driven
storytelling techniques to communicate the importance of
data to front-line employees or enhance products and service
offerings.
Dashboards and Reports
Track and use metrics to stay focused on achieving goals.
Organizations that use dashboards and reports find there is an
increased awareness around the collection and use of data.
However, it is important to share metrics strategically,
considering how you can use these dashboards to positively
impact behavior.
10Integrate Data into Daily Activities
These activities help
embed data into the
DNA of a company
and start making data
the native language
by which employees
communicate
effectively.
27. “Do Data Daily”
27
Assess Data Literacy Status
01
Develop a Data Literacy Strategy
02
Secure Executive Support
03
Identify Data Champions
04
Invest in a Data Literacy Foundation
05
Develop a Customized Data Literacy Curriculum
06
Use Data in Decision Making
07
Provide Access to Data
08
Hire Data Savvy Employees
09
Integrate Data into Daily Activities
10
The best way to learn a new language is through immersion and learning to speak data is no different. As you
build your foundational knowledge of data elements, it’s important to practice new and old skills every day.
Through repetition, you move from comprehension to data analysis and decision making. This process is most
successful when those learnings are paired with experts who can offer tricks, insights, and lessons learned.
To accomplish this, we recommend organizations DO DATA DAILYSM .
28. Thanks For Joining Us
We hope you enjoyed the presentation.
If you’d like to learn more about how to develop and
foster a data-literate workforce,
download our eBook.
https://sensecorp.com/10_steps_to_data_literacy/
DOWNLOAD EBOOK
www.sensecorp.com | marketing@sensecorp.com
29. THANK YOU
Contact me with Questions or Comments:
ALISSA SCHNEIDER
aschneider@sensecorp.com