If you have one or two files, you can take the time to manually work out what they are, what they contain, and how to get the useful bits out (probably....). However, this approach really doesn't scale, mechanical turks or no! Luckily, there are open source projects and libraries out there which can help, and which can scale!
In this talk, we'll first look at how we can work out what a given blob of 1s and 0s actually is, be it textual or binary. We'll then see how to extract common metadata from it, along with text, embedded resources, images, and maybe even the kitchen sink! We'll see how to use things like Apache Tika to do this, along with some other libraries to complement it. Once that part's all sorted, we'll look at how to roll this all out for a large-scale Search or Big Data setup, helping you turn those 1s and 0s into useful content at scale!
This talk was given at Berlin Buzzwords 2015
Data Modeling for Security, Privacy and Data ProtectionKaren Lopez
Karen Lopez (@datchick/InfoAdvisors) 90-minute presentation on Data Security, Data Privacy, Compliance and how data modelers should discover, assess, and monitor these important data management responsibilities.
Data is produced at a phenomenal rate
Our ability to store has grown
Users expect more sophisticated information
How?
Objective: Fit data to a model
Potential Result: Higher-level meta information that may not be obvious when looking at raw data
Similar terms
Exploratory data analysis
Data driven discovery
Deductive learning
Introduction To Hadoop | What Is Hadoop And Big Data | Hadoop Tutorial For Be...Simplilearn
This presentation about Hadoop will help you learn the basics of Hadoop and its components. First, you will see what is Big Data and the significant challenges in it. Then, you will understand how Hadoop solved those challenges. You will have a glance at the History of Hadoop, what is Hadoop, the different companies using Hadoop, the applications of Hadoop in different companies, etc. Finally, you will learn the three essential components of Hadoop – HDFS, MapReduce, and YARN, along with their architecture. Now, let us get started with Introduction to Hadoop.
Below topics are explained in this Hadoop presentation:
1. Big Data and its challenges
2. Hadoop as a solution
3. History of Hadoop
4. What is Hadoop
5. Applications of Hadoop
6. Components of Hadoop
7. Hadoop Distributed File System
8. Hadoop MapReduce
9. Hadoop YARN
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/introduction-to-big-data-and-hadoop-certification-training.
H2O World - Quora: Machine Learning Algorithms to Grow the World's Knowledge ...Sri Ambati
This document discusses how Quora uses machine learning to improve user experience. It summarizes that Quora aims to share and grow the world's knowledge using machine learning algorithms for tasks like answer ranking, feed ranking, topic and user recommendations, related question detection, and spam detection. It describes how Quora uses features about users, content, and their interactions to build models like logistic regression, decision trees and neural networks to complete these tasks at scale and through experimentation.
The document discusses introducing data mining concepts and tools in SQL Server 2012. It covers topics like data mining concepts, algorithms, structures, models, testing and validation. It specifically discusses how data mining differs from business intelligence by aiming to find patterns and trends to help with recommendations, sequences, groups and risk rather than structured decisions. It also covers the importance of data preparation steps like standardizing, normalizing and cleaning data before performing data mining.
A Statistician Walks into a Tech Company: R at a Rapidly Scaling Healthcare S...Work-Bench
This document summarizes a statistician's experience working at a healthcare technology startup that uses electronic health record data. It describes how the company initially had just one quantitative scientist but grew its team to include 70 software engineers and 10 quantitative scientists. It discusses how the company cultivated an R culture through internal packages, training, and hiring. It provides examples of when the company uses R for prototyping but implements in other languages for production, when R is used as a long-term solution, and when R and other languages are used in parallel for analysis.
This document discusses the importance of data preparation and understanding for data science projects. It notes that most of the work in any data project involves cleaning and preparing the data. The document emphasizes gaining both syntactic and semantic understanding of data through techniques like determining true data types, analyzing data density and distributions, and identifying equivalences. It also discusses how data understanding can reveal problems over time. Finally, it stresses the need for data science teams to be involved in the hands-on work of data transformation and understanding.
Data Modeling for Security, Privacy and Data ProtectionKaren Lopez
Karen Lopez (@datchick/InfoAdvisors) 90-minute presentation on Data Security, Data Privacy, Compliance and how data modelers should discover, assess, and monitor these important data management responsibilities.
Data is produced at a phenomenal rate
Our ability to store has grown
Users expect more sophisticated information
How?
Objective: Fit data to a model
Potential Result: Higher-level meta information that may not be obvious when looking at raw data
Similar terms
Exploratory data analysis
Data driven discovery
Deductive learning
Introduction To Hadoop | What Is Hadoop And Big Data | Hadoop Tutorial For Be...Simplilearn
This presentation about Hadoop will help you learn the basics of Hadoop and its components. First, you will see what is Big Data and the significant challenges in it. Then, you will understand how Hadoop solved those challenges. You will have a glance at the History of Hadoop, what is Hadoop, the different companies using Hadoop, the applications of Hadoop in different companies, etc. Finally, you will learn the three essential components of Hadoop – HDFS, MapReduce, and YARN, along with their architecture. Now, let us get started with Introduction to Hadoop.
Below topics are explained in this Hadoop presentation:
1. Big Data and its challenges
2. Hadoop as a solution
3. History of Hadoop
4. What is Hadoop
5. Applications of Hadoop
6. Components of Hadoop
7. Hadoop Distributed File System
8. Hadoop MapReduce
9. Hadoop YARN
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/introduction-to-big-data-and-hadoop-certification-training.
H2O World - Quora: Machine Learning Algorithms to Grow the World's Knowledge ...Sri Ambati
This document discusses how Quora uses machine learning to improve user experience. It summarizes that Quora aims to share and grow the world's knowledge using machine learning algorithms for tasks like answer ranking, feed ranking, topic and user recommendations, related question detection, and spam detection. It describes how Quora uses features about users, content, and their interactions to build models like logistic regression, decision trees and neural networks to complete these tasks at scale and through experimentation.
The document discusses introducing data mining concepts and tools in SQL Server 2012. It covers topics like data mining concepts, algorithms, structures, models, testing and validation. It specifically discusses how data mining differs from business intelligence by aiming to find patterns and trends to help with recommendations, sequences, groups and risk rather than structured decisions. It also covers the importance of data preparation steps like standardizing, normalizing and cleaning data before performing data mining.
A Statistician Walks into a Tech Company: R at a Rapidly Scaling Healthcare S...Work-Bench
This document summarizes a statistician's experience working at a healthcare technology startup that uses electronic health record data. It describes how the company initially had just one quantitative scientist but grew its team to include 70 software engineers and 10 quantitative scientists. It discusses how the company cultivated an R culture through internal packages, training, and hiring. It provides examples of when the company uses R for prototyping but implements in other languages for production, when R is used as a long-term solution, and when R and other languages are used in parallel for analysis.
This document discusses the importance of data preparation and understanding for data science projects. It notes that most of the work in any data project involves cleaning and preparing the data. The document emphasizes gaining both syntactic and semantic understanding of data through techniques like determining true data types, analyzing data density and distributions, and identifying equivalences. It also discusses how data understanding can reveal problems over time. Finally, it stresses the need for data science teams to be involved in the hands-on work of data transformation and understanding.
Ensuring Data Quality in Databricks Unleashing the Power of Great Expectation...Knoldus Inc.
In this session, join us on a journey to elevate your data quality standards as we explore the seamless integration of Great Expectations with Databricks. Discover how this powerful combination empowers data professionals to set, test, and enforce expectations on their data pipelines, ensuring accuracy and reliability.
ARMA Calgary Spring Seminar: The Nuts and Bolts of Metadata Tagging and Taxon...Concept Searching, Inc
Michael Pay, Concept Searching's Chief Technology Officer, will be speaking at the ARMA Calgary Spring Seminar on Tuesday April 25th, 2017 on:
The Nuts and Bolts of Metadata Tagging and Taxonomies Made Easy
Taxonomies are often thought of as hard to use and needing specialized applications or IT skills. Not so with Concept Searching’s unique technologies. Join Michael Paye, Concept Searching’s Chief Technology Officer, to see how taxonomies, auto-classification, and multi-term metadata generation unburden the IT team, eliminate end user tagging, and empower business users.
This session focuses on records management challenges in Office 365, Microsoft Exchange, and file shares, demonstrating:
• Automated multi-term metadata generation
• Unique taxonomy tools and interactive features, such as clue suggestion, instant feedback, and assigning weights to terms
• Flexible and simple reporting across the three repositories
• Automated records identification
• Tagging of content directly in Office 365 and on file shares
The document discusses the importance of metadata for publishers in the digital era. It defines metadata as "data about data" and explains that metadata has become critical for allowing computers and systems to communicate about content. Metadata impacts publisher processes by enabling content to reach the right audiences through various relationships and channels. The document provides examples of how metadata was essential for a drug reference product and a medical content provider to organize their content and drive various outputs. It emphasizes that metadata is just as, if not more, important than the raw content itself for digital publishing.
Turning XML to XLS on the JVM, without loosing your Sanity, with Groovygagravarr
This document discusses using the Groovy programming language to transform XML data into an Excel spreadsheet. It provides an overview of Groovy and how it can be used to easily parse and process XML. It then demonstrates using Groovy with the Apache POI library to generate an Excel file from the XML data. The document shows sample Groovy code for parsing the XML, extracting the necessary data, and writing rows and cells to create the Excel spreadsheet. It concludes by noting that while more code was needed for the full requirements, Groovy allowed efficiently processing the XML and generating the Excel output.
Ashley Ohmann--Data Governance Final 011315Ashley Ohmann
This presentation discusses enterprise data governance with Tableau. It defines data governance as processes that formally manage important data assets. The goals of data governance include establishing standards, processes, compliance, security, and metrics. Good data governance benefits an organization by improving accuracy, enabling better decisions with less waste. The presentation provides examples of how one organization improved data governance through stakeholder involvement, establishing metrics, building a data warehouse, and implementing Tableau for analytics. Key goals discussed are building trust, communicating validity, enabling access, managing metadata, provisioning rights, and maintaining compliance.
This document provides an overview of key concepts related to data and big data. It defines data, digital data, and the different types of digital data including unstructured, semi-structured, and structured data. Big data is introduced as the collection of large and complex data sets that are difficult to process using traditional tools. The importance of big data is discussed along with common sources of data and characteristics. Popular tools and technologies for storing, analyzing, and visualizing big data are also outlined.
Getting Started with Product Analytics - A 101 Implementation Guide for Begin...Vishrut Shukla
The document provides an overview of a workshop on getting started with product analytics for beginner and aspiring product managers, outlining why analytics is important for product development, how to plan an implementation by gathering requirements from stakeholders and choosing tools, and important considerations like backing up your primary analytics with a secondary implementation. It also includes examples, activities, and "commandments" or best practices for setting up an effective product analytics system.
The document discusses research and publication ethics and provides guidelines for responsible conduct of research. It outlines several key ethical principles researchers should follow, including honesty, objectivity, integrity, openness, care, respect for intellectual property and colleagues, confidentiality, responsible publication and mentoring, social responsibility, non-discrimination, competence, legality, and respect for animals and human subjects in research. It also lists and compares features of several free plagiarism detection tools available online.
This document discusses how Hadoop can be used to power a data lake and enhance traditional data warehousing approaches. It proposes a holistic data strategy with multiple layers: a landing area to store raw source data, a data lake to enrich and integrate data with light governance, a data science workspace for experimenting with new data, and a big data warehouse at the top level with fully governed and trusted data. Hadoop provides distributed storage and processing capabilities to support these layers. The document advocates a "polygot" approach, using the right tools like Hadoop, relational databases, and cloud platforms depending on the specific workload and data type.
Is Your Content Migration Strategy Garbage In, Garbage Out? WebinarConcept Searching, Inc
If you are migrating from SharePoint to SharePoint, SharePoint to Office 365, or SharePoint to a non-Microsoft product, we have the tools to get your content where you want it, and organize it at the same time.
Learn how to avoid the typical content migration pitfalls, and get your migration right.
Understand how to successfully migrate documents that may exist in multiple places, could be different revisions of the same document, or need to remain confidential when migrated.
Don’t just mass move your content. Attend to learn how to achieve intelligent migration.
• What is missing from typical migration strategies, even when using third party tools
• Why metadata generated from ‘content within context’ is important
• Designing a metadata schema aligned to your organization and its processes
• How conceptual metadata generation builds a consistent end user experience and decreases migration effort
• Maximizing ROI from your migration budget
Research data management for medical data with pyradigm.
Python data structure for biomedical data to manage multiple tables linked via patient info or other washable IDs. Allowing continuous validation, this data structure would improve ease of use as well as integrity of the dataset.
Data Profiling: The First Step to Big Data QualityPrecisely
Big data offers the promise of a data-driven business model generating new revenue and competitive advantage fueled by new business insights, AI, and machine learning. Yet without high quality data that provides trust, confidence, and understanding, business leaders continue to rely on gut instinct to drive business decisions.
The critical foundation and first step to deliver high quality data in support of a data-driven view that truly leverages the value of big data is data profiling - a proven capability to analyze the actual data content and help you understand what's really there.
View this webinar on-demand to learn five core concepts to effectively apply data profiling to your big data, assess and communicate the quality issues, and take the first step to big data quality and a data-driven business.
Amp Up Your Testing by Harnessing Test DataTechWell
The data tsunami is coming—or maybe it’s already here. Data science, big data, and machine learning are the buzzwords of the day. Data is changing our products and the way we build them, so we should also change the way we verify our products. In a world of increasing connectivity and accelerated deadlines, data can provide an edge. But what role should data play in assessing the quality of software? Where does it make sense to use data, and where is it inappropriate? Steve Rowe covers the history of how data fits into testing, explains why data is an important tool to have in your quality toolkit, and presents strategies for adding data to your testing plans and using it more effectively in your testing.
Machine Learning es una rama de la inteligencia artificial, que nos permite utilizar algoritmos que pueden operar sobre datos para determinar comportamiento, patrones, preferencias, etc.
Apache Mahout es una librería de código abierto que implementa una diversidad de algoritmos de Machine Learning, que bien pueden ser usados para construir un motor de recomendaciones para dirigir compras.
This document discusses how data and machine learning systems work, and some of their limitations. It makes three key points:
1. Machine learning systems are only as good as the data used to train them, and all data has some inherent bias which can negatively impact results if not addressed.
2. While large datasets and machine learning are powerful, humans still need to provide oversight to catch errors, prevent harm, and ensure systems don't behave in unexpected ways.
3. Thorough testing of systems with diverse datasets is needed to identify and address biases, anticipate problems, and ensure models are robust and represent their intended domains.
Effectively Capturing Paper and Digital Documents in your Existing Applicatio...J. Kevin Parker, CIP
In this webinar, we share best practices for the capturing of key information and data from paper and electronic documents and forms. We discuss:
- The value of must-have features including OCR, image and file compression, redaction, and group collaboration – without altering the original file
- Why all companies in any industry and of any size need to take advantage of these modernization efforts
- How simple solutions are readily available, with easy integration into your existing applications.
Presented September 19, 2018
Featured Speaker: Kevin Parker, CEO of Kwestix
Thanks to AIIM, the Association of Intelligent Information Management for the opportunity to present at this webinar.
Taxonomies are essential to making the web "go". Information architects and content strategists can use and promote taxonomy within their organizations to increase findability and usability of a website. Learn more about taxonomies and see some great examples.
On this slides, we tried to give an overview of advanced Data quality management (ADQM). To understand about DQ why important, and all those steps of DQ management.
In this fast-paced data-driven world, the fallout from a single data quality issue can cost thousands of dollars in a matter of hours. To catch these issues quickly, system monitoring for data quality requires a different set of strategies from other continuous regression efforts. Like a race car pit crew, you need detection mechanisms that not only don’t interfere with what you are monitoring but also allow for strategic analysis off-track. You need to use every second your subject is at rest to repair and clean up problems that could affect performance. As the systems in race cars vary, the tools and resources available to the data quality professional vary from one organization to the next. You need to be able to leverage the tools at hand to implement your solutions. Shauna Ayers and Catherine Cruz Agosto show you how to develop testing strategies to detect issues with data integration timing, operational dependencies, reference data management, and data integrity—even in production systems. See how you can leverage this testing to provide proactive notification alerts and feed business intelligence dashboards to communicate the health of your organization’s data systems to both operation support and non-technical personnel.
Our mission is to continuously seek, improve and understand the event stream processing techniques and architectures. Those techniques and understanding are necessary for situations where specific kind of action needs to be taken as soon as possible on a big scale. Many industries such as Banking, Telecom, Automotive, IoT have a need for the real-time processing and continuous computations over live streams of events .CROZ combined it’s expertise in dev and data to deliver a module that integrates into your existing Kafka environment and brings governance to streaming. Join the talk and find out what are event streaming and data governance, and why they are great together.
But we're already open source! Why would I want to bring my code to Apache?gagravarr
From ApacheCon Europe 2015 in Budapest
So, your business has already opened sourced some of its code? Great! Or you're thinking about it? That's fine! But now, someone's asking you about giving it to these Apache people? What's up with that, and why isn't just being open source enough?
In this talk, we'll look at several real world examples of where companies have chosen to contribute their existing open source code to the Apache Software Foundation. We'll see the advantages they got from it, the problems they faced along the way, why they did it, and how it helped their business. We'll also look briefly at where it may not be the right fit.
Wondering about how to take your business's open source involvement to the next level, and if contributing to projects at the Apache Software Foundation will deliver RoI, then this is the talk for you!
A presentation from ApacheCon Europe 2015 / Apache Big Data Europe 2015
Apache Tika detects and extracts metadata and text from a huge range of file formats and types. From Search to Big Data, single file to internet scale, if you've got files, Tika can help you get out useful information!
Apache Tika has been around for nearly 10 years now, and in that time, a lot has changed. Not only has the number of formats supported gone up and up, but the ways of using Tika have expanded, and some of the philosophies on the best way to handle things have altered with experience. Tika has gained support for a wide range of programming languages to, and more recently, Big-Data scale support, and ways to automatically compare effects of changes to the library.
Whether you're an old-hand with Tika looking to know what's hot or different, or someone new looking to learn more about the power of Tika, this talk will have something in it for you!
More Related Content
Similar to What's with the 1s and 0s? Making sense of binary data at scale - Berlin Buzzwords 2015
Ensuring Data Quality in Databricks Unleashing the Power of Great Expectation...Knoldus Inc.
In this session, join us on a journey to elevate your data quality standards as we explore the seamless integration of Great Expectations with Databricks. Discover how this powerful combination empowers data professionals to set, test, and enforce expectations on their data pipelines, ensuring accuracy and reliability.
ARMA Calgary Spring Seminar: The Nuts and Bolts of Metadata Tagging and Taxon...Concept Searching, Inc
Michael Pay, Concept Searching's Chief Technology Officer, will be speaking at the ARMA Calgary Spring Seminar on Tuesday April 25th, 2017 on:
The Nuts and Bolts of Metadata Tagging and Taxonomies Made Easy
Taxonomies are often thought of as hard to use and needing specialized applications or IT skills. Not so with Concept Searching’s unique technologies. Join Michael Paye, Concept Searching’s Chief Technology Officer, to see how taxonomies, auto-classification, and multi-term metadata generation unburden the IT team, eliminate end user tagging, and empower business users.
This session focuses on records management challenges in Office 365, Microsoft Exchange, and file shares, demonstrating:
• Automated multi-term metadata generation
• Unique taxonomy tools and interactive features, such as clue suggestion, instant feedback, and assigning weights to terms
• Flexible and simple reporting across the three repositories
• Automated records identification
• Tagging of content directly in Office 365 and on file shares
The document discusses the importance of metadata for publishers in the digital era. It defines metadata as "data about data" and explains that metadata has become critical for allowing computers and systems to communicate about content. Metadata impacts publisher processes by enabling content to reach the right audiences through various relationships and channels. The document provides examples of how metadata was essential for a drug reference product and a medical content provider to organize their content and drive various outputs. It emphasizes that metadata is just as, if not more, important than the raw content itself for digital publishing.
Turning XML to XLS on the JVM, without loosing your Sanity, with Groovygagravarr
This document discusses using the Groovy programming language to transform XML data into an Excel spreadsheet. It provides an overview of Groovy and how it can be used to easily parse and process XML. It then demonstrates using Groovy with the Apache POI library to generate an Excel file from the XML data. The document shows sample Groovy code for parsing the XML, extracting the necessary data, and writing rows and cells to create the Excel spreadsheet. It concludes by noting that while more code was needed for the full requirements, Groovy allowed efficiently processing the XML and generating the Excel output.
Ashley Ohmann--Data Governance Final 011315Ashley Ohmann
This presentation discusses enterprise data governance with Tableau. It defines data governance as processes that formally manage important data assets. The goals of data governance include establishing standards, processes, compliance, security, and metrics. Good data governance benefits an organization by improving accuracy, enabling better decisions with less waste. The presentation provides examples of how one organization improved data governance through stakeholder involvement, establishing metrics, building a data warehouse, and implementing Tableau for analytics. Key goals discussed are building trust, communicating validity, enabling access, managing metadata, provisioning rights, and maintaining compliance.
This document provides an overview of key concepts related to data and big data. It defines data, digital data, and the different types of digital data including unstructured, semi-structured, and structured data. Big data is introduced as the collection of large and complex data sets that are difficult to process using traditional tools. The importance of big data is discussed along with common sources of data and characteristics. Popular tools and technologies for storing, analyzing, and visualizing big data are also outlined.
Getting Started with Product Analytics - A 101 Implementation Guide for Begin...Vishrut Shukla
The document provides an overview of a workshop on getting started with product analytics for beginner and aspiring product managers, outlining why analytics is important for product development, how to plan an implementation by gathering requirements from stakeholders and choosing tools, and important considerations like backing up your primary analytics with a secondary implementation. It also includes examples, activities, and "commandments" or best practices for setting up an effective product analytics system.
The document discusses research and publication ethics and provides guidelines for responsible conduct of research. It outlines several key ethical principles researchers should follow, including honesty, objectivity, integrity, openness, care, respect for intellectual property and colleagues, confidentiality, responsible publication and mentoring, social responsibility, non-discrimination, competence, legality, and respect for animals and human subjects in research. It also lists and compares features of several free plagiarism detection tools available online.
This document discusses how Hadoop can be used to power a data lake and enhance traditional data warehousing approaches. It proposes a holistic data strategy with multiple layers: a landing area to store raw source data, a data lake to enrich and integrate data with light governance, a data science workspace for experimenting with new data, and a big data warehouse at the top level with fully governed and trusted data. Hadoop provides distributed storage and processing capabilities to support these layers. The document advocates a "polygot" approach, using the right tools like Hadoop, relational databases, and cloud platforms depending on the specific workload and data type.
Is Your Content Migration Strategy Garbage In, Garbage Out? WebinarConcept Searching, Inc
If you are migrating from SharePoint to SharePoint, SharePoint to Office 365, or SharePoint to a non-Microsoft product, we have the tools to get your content where you want it, and organize it at the same time.
Learn how to avoid the typical content migration pitfalls, and get your migration right.
Understand how to successfully migrate documents that may exist in multiple places, could be different revisions of the same document, or need to remain confidential when migrated.
Don’t just mass move your content. Attend to learn how to achieve intelligent migration.
• What is missing from typical migration strategies, even when using third party tools
• Why metadata generated from ‘content within context’ is important
• Designing a metadata schema aligned to your organization and its processes
• How conceptual metadata generation builds a consistent end user experience and decreases migration effort
• Maximizing ROI from your migration budget
Research data management for medical data with pyradigm.
Python data structure for biomedical data to manage multiple tables linked via patient info or other washable IDs. Allowing continuous validation, this data structure would improve ease of use as well as integrity of the dataset.
Data Profiling: The First Step to Big Data QualityPrecisely
Big data offers the promise of a data-driven business model generating new revenue and competitive advantage fueled by new business insights, AI, and machine learning. Yet without high quality data that provides trust, confidence, and understanding, business leaders continue to rely on gut instinct to drive business decisions.
The critical foundation and first step to deliver high quality data in support of a data-driven view that truly leverages the value of big data is data profiling - a proven capability to analyze the actual data content and help you understand what's really there.
View this webinar on-demand to learn five core concepts to effectively apply data profiling to your big data, assess and communicate the quality issues, and take the first step to big data quality and a data-driven business.
Amp Up Your Testing by Harnessing Test DataTechWell
The data tsunami is coming—or maybe it’s already here. Data science, big data, and machine learning are the buzzwords of the day. Data is changing our products and the way we build them, so we should also change the way we verify our products. In a world of increasing connectivity and accelerated deadlines, data can provide an edge. But what role should data play in assessing the quality of software? Where does it make sense to use data, and where is it inappropriate? Steve Rowe covers the history of how data fits into testing, explains why data is an important tool to have in your quality toolkit, and presents strategies for adding data to your testing plans and using it more effectively in your testing.
Machine Learning es una rama de la inteligencia artificial, que nos permite utilizar algoritmos que pueden operar sobre datos para determinar comportamiento, patrones, preferencias, etc.
Apache Mahout es una librería de código abierto que implementa una diversidad de algoritmos de Machine Learning, que bien pueden ser usados para construir un motor de recomendaciones para dirigir compras.
This document discusses how data and machine learning systems work, and some of their limitations. It makes three key points:
1. Machine learning systems are only as good as the data used to train them, and all data has some inherent bias which can negatively impact results if not addressed.
2. While large datasets and machine learning are powerful, humans still need to provide oversight to catch errors, prevent harm, and ensure systems don't behave in unexpected ways.
3. Thorough testing of systems with diverse datasets is needed to identify and address biases, anticipate problems, and ensure models are robust and represent their intended domains.
Effectively Capturing Paper and Digital Documents in your Existing Applicatio...J. Kevin Parker, CIP
In this webinar, we share best practices for the capturing of key information and data from paper and electronic documents and forms. We discuss:
- The value of must-have features including OCR, image and file compression, redaction, and group collaboration – without altering the original file
- Why all companies in any industry and of any size need to take advantage of these modernization efforts
- How simple solutions are readily available, with easy integration into your existing applications.
Presented September 19, 2018
Featured Speaker: Kevin Parker, CEO of Kwestix
Thanks to AIIM, the Association of Intelligent Information Management for the opportunity to present at this webinar.
Taxonomies are essential to making the web "go". Information architects and content strategists can use and promote taxonomy within their organizations to increase findability and usability of a website. Learn more about taxonomies and see some great examples.
On this slides, we tried to give an overview of advanced Data quality management (ADQM). To understand about DQ why important, and all those steps of DQ management.
In this fast-paced data-driven world, the fallout from a single data quality issue can cost thousands of dollars in a matter of hours. To catch these issues quickly, system monitoring for data quality requires a different set of strategies from other continuous regression efforts. Like a race car pit crew, you need detection mechanisms that not only don’t interfere with what you are monitoring but also allow for strategic analysis off-track. You need to use every second your subject is at rest to repair and clean up problems that could affect performance. As the systems in race cars vary, the tools and resources available to the data quality professional vary from one organization to the next. You need to be able to leverage the tools at hand to implement your solutions. Shauna Ayers and Catherine Cruz Agosto show you how to develop testing strategies to detect issues with data integration timing, operational dependencies, reference data management, and data integrity—even in production systems. See how you can leverage this testing to provide proactive notification alerts and feed business intelligence dashboards to communicate the health of your organization’s data systems to both operation support and non-technical personnel.
Our mission is to continuously seek, improve and understand the event stream processing techniques and architectures. Those techniques and understanding are necessary for situations where specific kind of action needs to be taken as soon as possible on a big scale. Many industries such as Banking, Telecom, Automotive, IoT have a need for the real-time processing and continuous computations over live streams of events .CROZ combined it’s expertise in dev and data to deliver a module that integrates into your existing Kafka environment and brings governance to streaming. Join the talk and find out what are event streaming and data governance, and why they are great together.
Similar to What's with the 1s and 0s? Making sense of binary data at scale - Berlin Buzzwords 2015 (20)
But we're already open source! Why would I want to bring my code to Apache?gagravarr
From ApacheCon Europe 2015 in Budapest
So, your business has already opened sourced some of its code? Great! Or you're thinking about it? That's fine! But now, someone's asking you about giving it to these Apache people? What's up with that, and why isn't just being open source enough?
In this talk, we'll look at several real world examples of where companies have chosen to contribute their existing open source code to the Apache Software Foundation. We'll see the advantages they got from it, the problems they faced along the way, why they did it, and how it helped their business. We'll also look briefly at where it may not be the right fit.
Wondering about how to take your business's open source involvement to the next level, and if contributing to projects at the Apache Software Foundation will deliver RoI, then this is the talk for you!
A presentation from ApacheCon Europe 2015 / Apache Big Data Europe 2015
Apache Tika detects and extracts metadata and text from a huge range of file formats and types. From Search to Big Data, single file to internet scale, if you've got files, Tika can help you get out useful information!
Apache Tika has been around for nearly 10 years now, and in that time, a lot has changed. Not only has the number of formats supported gone up and up, but the ways of using Tika have expanded, and some of the philosophies on the best way to handle things have altered with experience. Tika has gained support for a wide range of programming languages to, and more recently, Big-Data scale support, and ways to automatically compare effects of changes to the library.
Whether you're an old-hand with Tika looking to know what's hot or different, or someone new looking to learn more about the power of Tika, this talk will have something in it for you!
The ""Apache Way"" is the process by which Apache Software Foundation projects are managed. It has evolved over many years and has produced over 100 highly successful open source projects. But what is it and how does it work?
The other Apache Technologies your Big Data solution needsgagravarr
The document discusses many Apache projects relevant to big data solutions, including projects for loading and querying data like Pig and Gora, building MapReduce jobs like Avro and Thrift, cloud computing with LibCloud and DeltaCloud, and extracting information from unstructured data with Tika, UIMA, OpenNLP, and cTakes. It also mentions utility projects like Chemistry, JMeter, Commons, and ManifoldCF.
How Big is Big – Tall, Grande, Venti Data?gagravarr
Apache has a wide range of Big Data projects, some suitable for smaller problem sets, some which scale to huge problems. Today though, that one label "Big Data" can cause confusion for new users, as they may struggle to pick the right project for the right scale for their problem.
Do we need new titles for different kinds of Big Data? Does the buzz and VC funding cause confusion? Is the humble requirement dead? Or can we help new users better find the right Apache project for them?
If You Have The Content, Then Apache Has The Technology!gagravarr
This document provides a summary of 46 Apache content-related projects and 8 content-related incubating projects. It discusses projects for transforming and reading content like Apache PDFBox, POI, and Tika. Projects for text and language analysis like UIMA, OpenNLP, and Mahout. Projects that work with structured data and linked data like Any23, Stanbol, and Jena. Projects for data management and processing on Hadoop like MRQL, DataFu, and Falcon. Projects for serving content like HTTPD Server, TrafficServer, and Tomcat. Projects that focus on generating content like OpenOffice, Forrest, and Abdera. And projects for working with hosted content like Chemistry and ManifoldCF. The document
But We're Already Open Source! Why Would I Want To Bring My Code To Apache?gagravarr
So, your business has already opened sourced some of it's code? Great! But now, someone's asking you about giving it to these Apache people? What's up with that, and why isn't just being open source enough?
In this talk, we'll look at several real world examples of where companies have chosen to contribute their existing open source code to the Apache Software Foundation. We'll see the advantages they got from it, the problems they faced along the way, why they did it, and how it helped their business. We'll also look briefly at where it may not be the right fit.
Wondering about how to take your business's open source involvement to the next level, and if contributing to projects at the Apache Software Foundation will deliver RoI, then this is the talk for you!
What's With The 1S And 0S? Making Sense Of Binary Data At Scale With Tika And...gagravarr
This document provides an overview of Apache Tika, an open source toolkit for detecting and extracting metadata and structured text from various file formats. It discusses Tika's capabilities for detecting file types using filename extensions, magic bytes, and parsing file containers. It also describes how Tika extracts metadata, plain text, and XHTML from files and supports detecting text encodings and languages. The document outlines different ways to extend and customize Tika, as well as various options for integrating and running Tika programs.
What's with the 1s and 0s? Making sense of binary data at scale with Tika and...gagravarr
If you have one or two files, you can take the time to manually work out what they are, what they contain, and how to get the useful bits out (probably....). However, this approach really doesn't scale, mechanical turks or no! Luckily, there are Apache projects out there which can help!
In this talk, we'll first look at how we can work out what a given blob of 1s and 0s actually is, be it textual or binary. We'll then see how to extract common metadata from it, along with text, embedded resources, images, and maybe even the kitchen sink! We'll see how to do all of this with Apache Tika, and how to dive down to the underlying libraries (including its Apache friends like POI and PDFBox) for specialist cases. Finally, we'll look a little bit about how to roll this all out on a Big Data or Large-Search case.
From the Fast Feather Track at ApacheCon NA 2010 in Atlanta
This quick talk provides an overview of Apache Tika, looks at a new features and supported file formats. It then shows how to create a new parser, and finishes with using Tika from your own application.
An overview of all the different content related technologies at the Apache Software Foundation
Talk from ApacheCon NA 2010 in Atlanta in November 2010
Project Management: The Role of Project Dashboards.pdfKarya Keeper
Project management is a crucial aspect of any organization, ensuring that projects are completed efficiently and effectively. One of the key tools used in project management is the project dashboard, which provides a comprehensive view of project progress and performance. In this article, we will explore the role of project dashboards in project management, highlighting their key features and benefits.
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
Preparing Non - Technical Founders for Engaging a Tech AgencyISH Technologies
Preparing non-technical founders before engaging a tech agency is crucial for the success of their projects. It starts with clearly defining their vision and goals, conducting thorough market research, and gaining a basic understanding of relevant technologies. Setting realistic expectations and preparing a detailed project brief are essential steps. Founders should select a tech agency with a proven track record and establish clear communication channels. Additionally, addressing legal and contractual considerations and planning for post-launch support are vital to ensure a smooth and successful collaboration. This preparation empowers non-technical founders to effectively communicate their needs and work seamlessly with their chosen tech agency.Visit our site to get more details about this. Contact us today www.ishtechnologies.com.au
UI5con 2024 - Bring Your Own Design SystemPeter Muessig
How do you combine the OpenUI5/SAPUI5 programming model with a design system that makes its controls available as Web Components? Since OpenUI5/SAPUI5 1.120, the framework supports the integration of any Web Components. This makes it possible, for example, to natively embed own Web Components of your design system which are created with Stencil. The integration embeds the Web Components in a way that they can be used naturally in XMLViews, like with standard UI5 controls, and can be bound with data binding. Learn how you can also make use of the Web Components base class in OpenUI5/SAPUI5 to also integrate your Web Components and get inspired by the solution to generate a custom UI5 library providing the Web Components control wrappers for the native ones.
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
INTRODUCTION TO AI CLASSICAL THEORY TARGETED EXAMPLESanfaltahir1010
Image: Include an image that represents the concept of precision, such as a AI helix or a futuristic healthcare
setting.
Objective: Provide a foundational understanding of precision medicine and its departure from traditional
approaches
Role of theory: Discuss how genomics, the study of an organism's complete set of AI ,
plays a crucial role in precision medicine.
Customizing treatment plans: Highlight how genetic information is used to customize
treatment plans based on an individual's genetic makeup.
Examples: Provide real-world examples of successful application of AI such as genetic
therapies or targeted treatments.
Importance of molecular diagnostics: Explain the role of molecular diagnostics in identifying
molecular and genetic markers associated with diseases.
Biomarker testing: Showcase how biomarker testing aids in creating personalized treatment plans.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Real-world case study: Present a detailed case study showcasing the success of precision
medicine in a specific medical scenario.
Patient's journey: Discuss the patient's journey, treatment plan, and outcomes.
Impact: Emphasize the transformative effect of precision medicine on the individual's
health.
Objective: Ground the presentation in a real-world example, highlighting the practical
application and success of precision medicine.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions for handling and analyzing vast
datasets.
Visuals: Include graphics representing data management challenges and technological solutions.
Objective: Acknowledge the data-related challenges in precision medicine and highlight innovative solutions.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...kalichargn70th171
In today's fiercely competitive mobile app market, the role of the QA team is pivotal for continuous improvement and sustained success. Effective testing strategies are essential to navigate the challenges confidently and precisely. Ensuring the perfection of mobile apps before they reach end-users requires thoughtful decisions in the testing plan.
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Drona Infotech is a premier mobile app development company in Noida, providing cutting-edge solutions for businesses.
Visit Us For : https://www.dronainfotech.com/mobile-application-development/
DECODING JAVA THREAD DUMPS: MASTER THE ART OF ANALYSISTier1 app
Are you ready to unlock the secrets hidden within Java thread dumps? Join us for a hands-on session where we'll delve into effective troubleshooting patterns to swiftly identify the root causes of production problems. Discover the right tools, techniques, and best practices while exploring *real-world case studies of major outages* in Fortune 500 enterprises. Engage in interactive lab exercises where you'll have the opportunity to troubleshoot thread dumps and uncover performance issues firsthand. Join us and become a master of Java thread dump analysis!
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Odoo releases a new update every year. The latest version, Odoo 17, came out in October 2023. It brought many improvements to the user interface and user experience, along with new features in modules like accounting, marketing, manufacturing, websites, and more.
The Odoo 17 update has been a hot topic among startups, mid-sized businesses, large enterprises, and Odoo developers aiming to grow their businesses. Since it is now already the first quarter of 2024, you must have a clear idea of what Odoo 17 entails and what it can offer your business if you are still not aware of it.
This blog covers the features and functionalities. Explore the entire blog and get in touch with expert Odoo ERP consultants to leverage Odoo 17 and its features for your business too.
An Overview of Odoo ERP
Odoo ERP was first released as OpenERP software in February 2005. It is a suite of business applications used for ERP, CRM, eCommerce, websites, and project management. Ten years ago, the Odoo Enterprise edition was launched to help fund the Odoo Community version.
When you compare Odoo Community and Enterprise, the Enterprise edition offers exclusive features like mobile app access, Odoo Studio customisation, Odoo hosting, and unlimited functional support.
Today, Odoo is a well-known name used by companies of all sizes across various industries, including manufacturing, retail, accounting, marketing, healthcare, IT consulting, and R&D.
The latest version, Odoo 17, has been available since October 2023. Key highlights of this update include:
Enhanced user experience with improvements to the command bar, faster backend page loading, and multiple dashboard views.
Instant report generation, credit limit alerts for sales and invoices, separate OCR settings for invoice creation, and an auto-complete feature for forms in the accounting module.
Improved image handling and global attribute changes for mailing lists in email marketing.
A default auto-signature option and a refuse-to-sign option in HR modules.
Options to divide and merge manufacturing orders, track the status of manufacturing orders, and more in the MRP module.
Dark mode in Odoo 17.
Now that the Odoo 17 announcement is official, let’s look at what’s new in Odoo 17!
What is Odoo ERP 17?
Odoo 17 is the latest version of one of the world’s leading open-source enterprise ERPs. This version has come up with significant improvements explained here in this blog. Also, this new version aims to introduce features that enhance time-saving, efficiency, and productivity for users across various organisations.
Odoo 17, released at the Odoo Experience 2023, brought notable improvements to the user interface and added new functionalities with enhancements in performance, accessibility, data analysis, and management, further expanding its reach in the market.
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.