Big Data - Michalis Grigoratos - Talent4Tech
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Big Data involves tapping into diverse data sets to find unknown relationships and make data-driven business decisions. The process involves acquiring all available data, organizing and analyzing the large data using massive parallelism, and making real-time decisions based on the insights gleaned. However, accurately capturing data is challenging, and failures to do so consistently can render later analysis meaningless due to garbage in resulting in garbage out.
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Learning Objectives:
Understanding contextually why data governance can be tricky for most organizations
Demonstrate a variety of “storytelling” techniques
How to use “worst practices” to your advantage
Understanding foundational data governance concepts based on the Data Management Body of Knowledge (DMBOK)
Taking away several novel but tangible examples of generating business value through data governance
Austrade Presentation - Big Data the New Oil (Microsoft draft)
1. Exponential growth in data created, collected, and stored has led to a 10x increase in "situation awareness" with big data, requiring rethinking of decision-making processes.
2. Big data is not a "silver bullet" but a new problem-solving philosophy that seeks evidence-based decisions to increase the tempo and speed of decisions in both the private sector and government.
3. Big data will have top-line and bottom-line implications for companies and far-reaching effects on the economy through increased use of analytics, machine learning, and data visualization techniques on large datasets.
The Rise of Open Data
An exploration of how openly shared, passively collected, and persistent personal data is providing individuals with scaffolding and feedback for complex tasks. The resulting technosocial impact is a shifting of the locus of control from centralized management and production of resources, decentralizing towards individuals.
What is Big Data?
This document discusses big data, defining it as large volumes of diverse data that come in at high velocity, requiring new techniques and technologies to capture, store, distribute, manage and analyze the data to extract value and enable better decision making. It notes that 90% of data in the world has been created in just the past two years, and data is doubling every two years. Big data tools are needed to analyze both structured and unstructured data from a variety of internal and external sources to gain business insights. Examples provided discuss using big data in insurance to identify risk patterns and sales leads, and in banking to analyze customer transactions and enrich customer profiles.
12 nt cviz
1) The document discusses a session on data visualization techniques for social change. It provides an agenda that covers measuring networked nonprofits, using data for assessment, learning and management, and communications and advocacy.
2) The session discusses how visualizing data through techniques like maps, placemats, dashboards and research findings can help nonprofits better understand and communicate information.
3) Effective data visualization follows design principles like maximizing data ink, using color and contrast effectively, allowing the purpose to guide the medium used, and incorporating classic graphic design elements. Visuals can help nonprofits evolve to more impactful communication.
Big Data v2.pptx
Big data brings changes in thinking and business. It introduces new challenges for enterprises as well.
The document discusses the key features of big data including volume, velocity, variety and veracity. It provides examples of big data sources and applications. Benefits of big data include enabling predictions based on overall data rather than samples.
Big data is changing how businesses operate by creating new types of data-focused and technology companies. However, enterprises face challenges such as unclear big data needs, data silos, quality issues and talent shortages in deploying big data. Data security and privacy are also major considerations.
Data Management for Citizen Science
The document discusses challenges and opportunities for data management in citizen science projects. It identifies developing data management plans, establishing data policies, developing supporting cyberinfrastructure or technology platforms, and ensuring data quality as key issues. A survey of citizen science projects found the greatest dissatisfaction with processes for sharing data and presenting results, but that data management planning was better than average. Top priorities for improvement included tools for analyzing, visualizing, documenting and describing data, as well as training. The presentation calls on USGS to lead by example in promoting data sharing, developing clear and reusable policies and platforms, and demonstrating best practices for data quality.
How to make data actionable for business
This workshop was conducted at AdTech Bangalore where the speaker walked through how data can be made actionable for business.
Sgcp14dunlea
The document discusses how utilities are increasingly collecting and generating large amounts of data from smart meters and other sensors. It notes that utilities must learn to leverage this "big data" by acquiring, organizing, and analyzing different types of structured and unstructured data from various sources in order to make more informed operational and business decisions. Effective use of big data can help utilities optimize operations, improve customer experience, and increase business performance. However, most utilities currently underutilize data analytics capabilities and face challenges in integrating diverse data sources and systems. The document advocates for a well-designed data management platform that can consolidate utility data to facilitate deeper analysis and more valuable insights.
Krithi talk-impact
This document provides an overview of a course on data warehousing, decision support, and data mining. It discusses data warehousing architectures and how data is extracted, transformed, and loaded from various sources into the data warehouse. It also covers operational vs analytical systems and challenges with data quality and integration when loading the warehouse. Examples from Walmart's data warehouse implementation are provided.
Prediktiv analys och kundlojalitet
Vilka framgångsfaktorer har allra störst inverkan på skapandet av den optimala kundupplevelsen? Utnyttja denna information för att på ett smartare sätt förstå, förutsäga och påverka kundernas beteende.
Robert Moberg, Prediktiv Analysexpert, IBM Sverige
THE 3V's OF BIG DATA: VARIETY, VELOCITY, AND VOLUME from Structure:Data 2012
The document discusses the 3 V's of big data: volume, velocity, and variety. It provides examples of how each V impacts data analysis and storage. It also discusses how text data has been a major driver of big data growth and challenges. The key challenges are processing large and diverse datasets quickly enough to keep up with real-time data streams and demands.
Similar to Big Data - Michalis Grigoratos - Talent4Tech (20)
Using Big Data to create a data drive organization
Using Big Data to create a data drive organization
Ibm big data ibm marriage of hadoop and data warehousing
Ibm big data ibm marriage of hadoop and data warehousing
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)
Big data analytics - Introduction to Big Data and Hadoop
Big data analytics - Introduction to Big Data and Hadoop
DataEd Online: Unlock Business Value through Data Governance
DataEd Online: Unlock Business Value through Data Governance
Data-Ed: Unlock Business Value through Data Governance
Data-Ed: Unlock Business Value through Data Governance
Austrade Presentation - Big Data the New Oil (Microsoft draft)
Austrade Presentation - Big Data the New Oil (Microsoft draft)
THE 3V's OF BIG DATA: VARIETY, VELOCITY, AND VOLUME from Structure:Data 2012
THE 3V's OF BIG DATA: VARIETY, VELOCITY, AND VOLUME from Structure:Data 2012
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GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
Discover the Unseen: Tailored Recommendation of Unwatched Content
The session shares how JioCinema approaches ""watch discounting."" This capability ensures that if a user watched a certain amount of a show/movie, the platform no longer recommends that particular content to the user. Flawless operation of this feature promotes the discover of new content, improving the overall user experience.
JioCinema is an Indian over-the-top media streaming service owned by Viacom18.
Northern Engraving | Nameplate Manufacturing Process - 2024
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
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AI in the Workplace Reskilling, Upskilling, and Future Work.pptx
Discover how AI is transforming the workplace and learn strategies for reskilling and upskilling employees to stay ahead. This comprehensive guide covers the impact of AI on jobs, essential skills for the future, and successful case studies from industry leaders. Embrace AI-driven changes, foster continuous learning, and build a future-ready workforce.
Read More - https://bit.ly/3VKly70
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Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
ScyllaDB Tablets: Rethinking Replication
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
What is an RPA CoE? Session 2 – CoE Roles
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
What is an RPA CoE? Session 1 – CoE Vision
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
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Must Know Postgres Extension for DBA and Developer during Migration
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
AWS Certified Solutions Architect Associate (SAA-C03)
AWS Certified Solutions Architect Associate (SAA-C03)
Session 1 - Intro to Robotic Process Automation.pdf
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
"Choosing proper type of scaling", Olena Syrota
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
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Astute Business Solutions | Oracle Cloud Partner |
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Discover the Unseen: Tailored Recommendation of Unwatched Content
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Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
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Big Data - Michalis Grigoratos - Talent4Tech
- 8. Big Data Is About… Tapping into diverse data sets Finding and mone1zing unknown rela1onships Data driven business decisions
- 9. Big Data in Action DECIDE ACQUIRE Make Be=er Decisions Using Big Data ANALYZE ORGANIZE
- 10. Big Data in Action DECIDE ACQUIRE Acquire all available data ANALYZE ORGANIZE
- 11. Big Data in Action DECIDE ACQUIRE Organize and dis1ll big data using massive parallelism ANALYZE ORGANIZE
- 12. Big Data in Action DECIDE ACQUIRE Analyze all your data, at once ANALYZE ORGANIZE
- 13. Big Data in Action DECIDE ACQUIRE Decide based on real-‐1me big data ANALYZE ORGANIZE
- 19. Big Data Simplifies Sustainability Cost Scenarios • Which clean energy projects make sense to install in different manufacturing or office loca1ons? • Which sustainability project will give your team the quickest payback when it comes to reducing environmental impact?
- 20. The Problem we face Today […] the root of the true problems with big data are oXen not in how or what tools we use to analyze the data, but more so in how we capture, or fail to capture it in the first place. In essence, our failure to capture the data accurately and consistently oXen renders analysis of it a meaningless exercise due to the Garbage In = Garbage Out (GIGO) principle.
- 25. Thank You