This webinar discusses choosing the right database for organizations. It will cover industry trends driving data and database evolution, real-world use cases where speed and scale are important, and an architecture overview. Speakers from Forrester and Aerospike will discuss how new applications are challenging traditional databases and how Aerospike's in-memory database provides extremely high performance for large-scale, data-intensive workloads. The agenda includes an industry overview, tips for choosing a database, how data has evolved, examples where low latency is critical, and a question and answer session.
Tectonic Shift: A New Foundation for Data Driven BusinessAerospike, Inc.
The document discusses how Aerospike provides a high performance NoSQL database that can power real-time applications at scale. It focuses on use cases in industries like retail, financial services, telecom, adtech, and internet that have mission critical applications requiring speed, scale, and affordability. The document highlights how Aerospike delivers dramatic total cost of ownership advantages through 10-100x performance improvements at lower costs per transaction compared to other solutions.
Flash Economics and Lessons learned from operating low latency platforms at h...Aerospike, Inc.
The document discusses requirements for internet enterprises, including responding to interactions in real-time, determining user intent based on context, responding immediately using big data, and ensuring systems never go down. It then discusses Aerospike's in-memory database capabilities for handling high transaction volumes with low latency and unlimited scalability. Finally, it outlines lessons learned from operating high performance systems, including keeping architectures simple, automating operations, and separating online and offline workloads.
The document discusses Pure Storage and its all-flash storage solutions. It provides 10 reasons to choose Pure, including that Pure storage is built for NVMe, has a disruptively simple architecture, proven high availability of 99.9999%, AI-driven management and predictive support, application support, self-protecting storage, an open full stack, Evergreen upgrades, and industry recognition as a leader in Gartner reports. The document then discusses Pure's business model, customer experience, technology advantages, and culture that emphasize customer satisfaction.
This document discusses Dell's solutions for big data and analytics workloads. It describes Dell's portfolio for unstructured analytics including storage, servers, and reference architectures. It also outlines Dell's vision for a unified streaming and batch analytics platform called Project Nautilus that would integrate Isilon storage with real-time stream processing.
Startup Case Study: Leveraging the Broad Hadoop Ecosystem to Develop World-Fi...DataWorks Summit
Back in 2014, our team set out to change the way the world exchanges and collaborates with data. Our vision was to build a single tenant environment for multiple organisations to securely share and consume data. And we did just that, leveraging multiple Hadoop technologies to help our infrastructure scale quickly and securely.
Today Data Republic’s technology delivers a trusted platform for hundreds of enterprise level companies to securely exchange, commercialise and collaborate with large datasets.
Join Head of Engineering, Juan Delard de Rigoulières and Senior Solutions Architect, Amin Abbaspour as they share key lessons from their team’s journey with Hadoop:
* How a startup leveraged a clever combination of Hadoop technologies to build a secure data exchange platform
* How Hadoop technologies helped us deliver key solutions around governance, security and controls of data and metadata
* An evaluation on the maturity and usefulness of some Hadoop technologies in our environment: Hive, HDFS, Spark, Ranger, Atlas, Knox, Kylin: we've use them all extensively.
* Our bold approach to expose APIs directly to end users; as well as the challenges, learning and code we created in the process
* Learnings from the front-line: How our team coped with code changes, performance tuning, issues and solutions while building our data exchange
Whether you’re an enterprise level business or a start-up looking to scale - this case study discussion offers behind-the-scenes lessons and key tips when using Hadoop technologies to manage data governance and collaboration in the cloud.
Speakers:
Juan Delard De Rigoulieres, Head of Engineering, Data Republic Pty Ltd
Amin Abbaspour, Senior Solutions Architect, Data Republic
NVMe and all-flash systems can solve any performance, floor space and energy problems. At least this is the marketing message many vendors and analysts spread today – but actually, sounds too good to be true, right?
Like always in real life, there is no clear black or white, but some circumstances you should be aware of – especially if you intend to leverage these technologies.
You may ask yourself: Do I need to rip and replace my existing storage? What is the best way to integrate both? What benefits do I receive?
Well, just join our brief webinar, which also includes a live demo and audience Q&A so you can get the most out of these technologies, make your storage great again and discover:
• How to integrate Flash over NVMe in real life
• How to benefit of some Flash/NVMe for your entire applications
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFiDataWorks Summit
Utilizing Apache NiFi we read various open data REST APIs and camera feeds to ingest crime and related data real-time streaming it into HBase and Phoenix tables. HBase makes an excellent storage option for our real-time time series data sources. We can immediately query our data utilizing Apache Zeppelin against Phoenix tables as well as Hive external tables to HBase.
Apache Phoenix tables also make a great option since we can easily put microservices on top of them for application usage. I have an example Spring Boot application that reads from our Philadelphia crime table for front-end web applications as well as RESTful APIs.
Apache NiFi makes it easy to push records with schemas to HBase and insert into Phoenix SQL tables.
Resources:
https://community.hortonworks.com/articles/54947/reading-opendata-json-and-storing-into-phoenix-tab.html
https://community.hortonworks.com/articles/56642/creating-a-spring-boot-java-8-microservice-to-read.html
https://community.hortonworks.com/articles/64122/incrementally-streaming-rdbms-data-to-your-hadoop.html
Ingesting Data at Blazing Speed Using Apache OrcDataWorks Summit
Big SQL is a SQL engine for Hadoop that excels at performance and scalability at high concurrency. Big SQL complements and integrates with Apache Hive for both data and metadata. An architecture that separates compute from storage allows Big SQL to support multiple open data formats natively. Until recently, Parquet provided a significant performance advantage over other data formats for SQL on Hadoop. The landscape changed when ORC became a top level Apache project independent from Hive. Gone were the days of reading ORC files using slow, single-row-at-a-time Hive Serdes. The new vectorized APIs in the Apache ORC libraries make it possible to ingest ORC data at blazing speed. This talk is about the journey leading to ORC taking the crown of best performing data format for Big SQL away from Parquet. We'll have a look under the hood at the architecture of Big SQL ORC readers, and how to tune them. We'll share lessons learned in walking the fine line between maximizing performance at scale and avoiding dreaded Java OOMs . You'll learn the techniques that SQL engines use for fast data ingestion, so that you can leverage the full potential of Apache ORC in any application.
Speaker:
Gustavo Arocena, Big Data Architect, IBM
Apache Ignite vs Alluxio: Memory Speed Big Data AnalyticsDataWorks Summit
Apache Ignite vs Alluxio: Memory Speed Big Data Analytics - Apache Spark’s in memory capabilities catapulted it as the premier processing framework for Hadoop. Apache Ignite and Alluxio, both high-performance, integrated and distributed in-memory platform, takes Apache Spark to the next level by providing an even more powerful, faster and scalable platform to the most demanding data processing and analytic environments.
Speaker
Irfan Elahi, Consultant, Deloitte
The document discusses different strategies for horizontally scaling databases, including simple sharding, hashed sharding, and master-slave architectures. It describes Aerospike's approach of "smart partitioning", which balances data automatically, hides complexity from clients, and provides redundancy and failover. The key advantages are linear scalability, high availability even during maintenance, and the ability to handle catastrophic failures through multi-datacenter replication that can withstand outages and disasters.
Better performance and cost effectiveness empower better results in the cognitive era. For more information, visit: http://www.ibm.com/systems/power/hardware/linux-lc.html
In memory computing principles by Mac Moore of GridGainData Con LA
This document provides an overview of in-memory computing principles and GridGain's in-memory data fabric technology. It discusses why in-memory computing is needed to handle today's data volumes and velocities, how architectures have evolved from traditional databases to in-memory data grids, key considerations for in-memory data grids, use cases for GridGain's technology, and highlights of GridGain's Release 6.5 including cross-language interoperability and dynamic schema changes.
Insights into Real-world Data Management ChallengesDataWorks Summit
Oracle began with the belief that the foundation of IT was managing information. The Oracle Cloud Platform for Big Data is a natural extension of our belief in the power of data. Oracle’s Integrated Cloud is one cloud for the entire business, meeting everyone’s needs. It’s about Connecting people to information through tools which help you combine and aggregate data from any source.
This session will explore how organizations can transition to the cloud by delivering fully managed and elastic Hadoop and Real-time Streaming cloud services to built robust offerings that provide measurable value to the business. We will explore key data management trends and dive deeper into pain points we are hearing about from our customer base.
The rapid growth of in-memory compute applications is not surprising given the tremendous performance gains they can offer. Jobs that used to take hours can now take minutes or seconds as they are no longer subject to the rotational and seek latencies of spinning media. While Flash memory provide some relief, it is still a hundred times slower than the DRAM that in-memory compute applications utilize as their primary storage.
One drawback to in-memory compute applications is the high cost associated with DRAM. Not only are the acquisition costs an order of magnitude more expensive than Flash, DRAM consumes far more power. Power can be a significant issue in data centers besides contributing a major part to the operational costs. In addition, a single server has limited capacity for DRAM and datasets that are larger, need to find an alternate solution or cope with the nuisance of sharding. Furthermore, in order to utilize the maximum capacity of DRAM in a server, higher cost DRAM needs to be installed further escalating the cost of compute.
We discuss a paradigm to allow in-memory computing applications to extend their capacity by utilizing Flash memory; often with minimal performance loss. We give examples of applications that have been modified to utilize the paradigm and show performance comparisons. We also discuss TCO and the relative cost per transaction of the different solutions.
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiDataWorks Summit
At Comcast, our team has been architecting a customer experience platform which is able to react to near-real-time events and interactions and deliver appropriate and timely communications to customers. By combining the low latency capabilities of Apache Flink and the dataflow capabilities of Apache NiFi we are able to process events at high volume to trigger, enrich, filter, and act/communicate to enhance customer experiences. Apache Flink and Apache NiFi complement each other with their strengths in event streaming and correlation, state management, command-and-control, parallelism, development methodology, and interoperability with surrounding technologies. We will trace our journey from starting with Apache NiFi over three years ago and our more recent introduction of Apache Flink into our platform stack to handle more complex scenarios. In this presentation we will compare and contrast which business and technical use cases are best suited to which platform and explore different ways to integrate the two platforms into a single solution.
Spark + Flashblade: Spark Summit East talk by Brian GoldSpark Summit
Modern infrastructure and applications generate extraordinary volumes of log and telemetry data. At Pure Storage, we know this first hand: we have over 5PB of log data from production customers running our all-flash storage systems, from our engineering testbeds, and from test stations at manufacturing partners. Every part of our company — from engineering to sales — now depends on the insights we gather from this data. Given the diversity of our end users, it’s no surprise that our analysis tools comprise a broad mix of reporting queries, stream-processing operations, ad-hoc analyses, and deeper machine-learning algorithms. In this session, we will cover lessons learned from scaling our data warehouse and how we are leveraging Apache Spark’s capabilities as a central hub to meet our analytics demands.
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerDataWorks Summit
Companies are increasingly moving to the cloud to store and process data. One of the challenges companies have is in securing data across hybrid environments with easy way to centrally manage policies. In this session, we will talk through how companies can use Apache Ranger to protect access to data both in on-premise as well as in cloud environments. We will go into details into the challenges of hybrid environment and how Ranger can solve it. We will also talk through how companies can further enhance the security by leveraging Ranger to anonymize or tokenize data while moving into the cloud and de-anonymize dynamically using Apache Hive, Apache Spark or when accessing data from cloud storage systems. We will also deep dive into the Ranger’s integration with AWS S3, AWS Redshift and other cloud native systems. We will wrap it up with an end to end demo showing how policies can be created in Ranger and used to manage access to data in different systems, anonymize or de-anonymize data and track where data is flowing.
RedisConf17 - Redis Enterprise on IBM Power SystemsRedis Labs
Redis Labs Enterprise Cluster provides a high performance NoSQL data store. It can be deployed on IBM Power Systems servers to take advantage of their high memory bandwidth and cache capabilities. This provides significantly higher performance and lower costs than deploying on x86 servers. Specifically, a Redis Labs cluster on Power Systems can achieve 24x lower infrastructure needs, 2x lower costs, and use 6x less rack space compared to a typical x86 deployment.
The document discusses HP's strategy to provide IT infrastructure as a service (ITaaS). It outlines HP's portfolio of converged storage solutions including 3PAR, StoreOnce, StoreAll, and StoreVirtual. These solutions provide scalable, software-defined storage that can be deployed from small to large organizations to enable private and public cloud storage services. HP storage solutions are designed to improve efficiency, performance and manageability while reducing costs compared to traditional SAN solutions.
Avoiding Log Data Overload in a CI/CD System While Streaming 190 Billion Even...DataWorks Summit
Learn how Pure Storage engineering manages streaming 190B log events per day and makes use of that deluge of data in our continuous integration (CI) pipeline. Our test infrastructure runs over 70,000 tests per day creating a large triage problem that would require at least 20 triage engineers. Instead, Spark's flexible computing platform allows us to write a single application for both streaming and batch jobs to understand the state of our CI pipeline for our team of 3 triage engineers. Using encoded patterns, Spark indexes log data for real-time reporting (Streaming), uses Machine Learning for performance modeling and prediction (Batch job), and finds previous matches for newly encoded patterns (Batch job). Resource allocation in this mixed environment can be challenging; a containerized Spark cluster deployment, and disaggregated compute and storage layers allow us to programmatically shift compute resources between the streaming and batch applications.. This talk will go over design decisions to meet SLAs of streaming and batching in hardware, data layout, access patterns, and containers strategy. We will also go over the challenges, lessons learned, and best practices for similar data pipelines.
Speaker
Joshua Robinson, JOSHUA ROBINSON
Founding Engineer
Pure Storage
This presentation breaks down the Aerospike Key Value Data Access. It covers the topics of Structured vs Unstructured Data, Database Hierarchy & Definitions as well as Data Patterns.
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/HourAerospike, Inc.
Rajkumar Iyer and Sunil Sayyaparaju reveal how their team proved that cost-effective, high performance in the cloud isn’t a myth. They will walk through the 10-step process to efficiently set up high-performance instances on Amazon EC2 with Aerospike.
The document discusses improving performance in Aerospike systems. It analyzes performance at the client level, network level, and Aerospike node level. Some key factors that can impact performance are CPU usage, number of network connections, bandwidth, transactions per second, and storage I/O. The document provides commands to monitor these factors and suggests potential remedies such as adding nodes, SSDs, faster network equipment, or load balancing.
In this presentation, Glassbeam Principal Architect Mohammad Guller gives an overview of Spark, and discusses why people are replacing Hadoop MapReduce with Spark for batch and stream processing jobs. He also covers areas where Spark really shines and presents a few real-world Spark scenarios. In addition, he reviews some misconceptions about Spark.
Learn how Aerospike's Hybrid Memory Architecture brings transactions and analytics together to power real-time Systems of Engagement ( SOEs) for companies across AdTech, financial services, telecommunications, and eCommerce. We take a deep dive into the architecture including use cases, topology, Smart Clients, XDR and more. Aerospike delivers predictable performance, high uptime and availability at the lowest total cost of ownership (TCO).
El documento presenta la información de un maestro de historia de México en una secundaria, incluyendo sus responsabilidades docentes, filosofía de enseñanza-aprendizaje, metodología, esfuerzos para mejorar su enseñanza y resultados. Describe su enfoque de evitar la memorización y enfocarse en la comprensión, análisis y relación del pasado con el presente a través de diversos recursos y tecnología. Los resultados muestran promedios entre 6.5 y 8.5 para varios grupos.
This is a presentation from 2011 highlighting the possibilities of IT in private cardiology practice. It is of historical value but touches on early fundamental concepts of digitalization of a private practice in the field of cardiology.
Presentation from Adtech Hacked
Aerospike's highly reliable and scalable database, using NoSQL and In-memory technology, presentation slides given at Stack Exchange on April 10th with NSOne and advertising technology luminaries.
AdTech Gets Hacked in Lower Manhattan
Stack Exchange, 110 William St 28th Floor,
New York, NY 10038
Dokumen tersebut membahas perbandingan perhitungan efisiensi antara pembangkit listrik tenaga uap konvensional yang menggunakan bahan bakar fosil seperti minyak, gas, dan batubara dengan pembangkit listrik tenaga nuklir. Perhitungan efisiensi PLTU dilakukan dengan metode laju kalor, sedangkan untuk PLTN menggunakan data efisiensi yang terbukti untuk BWR, PWR, PHWR, dan HTR. Hasilnya menunjuk
The document provides an overview of Aerospike, a real-time database vendor, from their perspective. It discusses the different types of database workloads, including transactions, analytics, and real-time big data. It outlines the challenges of handling high transaction volumes at low latency while scaling data size. The document then describes Aerospike's in-memory architecture, synchronous replication for consistency, and horizontal and vertical scaling capabilities. Several case studies of companies using Aerospike in production are also mentioned.
This document discusses medical apps and their use in clinical practice. It describes how wireless sensors, genomics, mobile connectivity and other digital technologies are converging into individualized medicine. It notes that patients want apps that provide access to test results and health records via mobile devices. The document outlines pitfalls in medical app design and barriers to adoption from both physician and patient perspectives. It then describes Happtique's new app certification program, which establishes standards for app safety, operability, privacy and content.
How to Get a Game Changing Performance Advantage with Intel SSDs and AerospikeAerospike, Inc.
Frank Ober of Intel’s Solutions Group will review how he achieved 1+ million transactions per second on a single dual socket Xeon Server with SSDs using the open source tools of Aerospike for benchmarking. The presentation will include a live demo showing the performance of a sample system. We will cover:
The state of Key-value Stores on modern SSDs.
What choices you make in your selection process of hardware that will most benefit a consistent deployment of Aerospike.
How to run an Aerospike mesh on a single machine.
How to work replication of that mesh, and what values allow for maximum threading and scale.
We will also focus on some key learnings and the Total Cost of Ownership choices that will make your deployment more effective long term.
Building Confidence in Big Data - IBM Smarter Business 2013 IBM Sverige
Success with big data comes down to confidence. Without confidence in the underlying data, decision makers may not trust and act on analytic insight. You need confidence in your data – that it’s correct, trusted, and protected through automated integration, visual context, and agile governance. You need confidence in your ability to accelerate time to value, with fast deployments of big data appliances. Learn how clients have succeeded with big data by building confidence in their data, ability to deploy, and skills. Presenter: David Corrigan, Big Data specialist, IBM. Mer från dagen på http://bit.ly/sb13se
A Key to Real-time Insights in a Post-COVID World (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2EpHGyd
Presented at Data Champions, Online Asia 2020
Businesses and individuals around the world are experiencing the impact of a global pandemic. With many workers and potential shoppers still sequestered, COVID-19 is proving to have a momentous impact on the global economy. Regardless of the current situation and post-pandemic era, real-time data becomes even more critical to healthcare practitioners, business owners, government officials, and the public at large where holistic and timely information are important to make quick decisions. It enables doctors to make quick decisions about where to focus the care, business owners to alter production schedules to meet the demand, government agencies to contain the epidemic, and the public to be informed about prevention.
In this on-demand session, you will learn about the capabilities of data virtualization as a modern data integration technique and how can organisations:
- Rapidly unify information from disparate data sources to make accurate decisions and analyse data in real-time
- Build a single engine for security that provides audit and control by geographies
- Accelerate delivery of insights from your advanced analytics project
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
The document discusses the future of data management through the use of an enterprise data hub (EDH). It notes that an EDH provides a centralized platform for ingesting, storing, exploring, processing, analyzing and serving diverse data from across an organization on a large scale in a cost effective manner. This approach overcomes limitations of traditional data silos and enables new analytic capabilities.
Horses for Courses: Database RoundtableEric Kavanagh
The blessing and curse of today's database market? So many choices! While relational databases still dominate the day-to-day business, a host of alternatives has evolved around very specific use cases: graph, document, NoSQL, hybrid (HTAP), column store, the list goes on. And the database tools market is teeming with activity as well. Register for this special Research Webcast to hear Dr. Robin Bloor share his early findings about the evolving database market. He'll be joined by Steve Sarsfield of HPE Vertica, and Robert Reeves of Datical in a roundtable discussion with Bloor Group CEO Eric Kavanagh. Send any questions to info@insideanalysis.com, or tweet with #DBSurvival.
Why Infrastructure Matters for Big Data & AnalyticsRick Perret
This document discusses how infrastructure is important for big data and analytics. It provides examples of how access, speed, and availability of infrastructure impact organizations' ability to gain insights from data. Specifically, it discusses how IBM's infrastructure capabilities such as data optimization, parallel processing, low latency, and scalability help companies like Bank of Quanzhou, Coca Cola Bottling, and Sui Southern Gas Company optimize access to data, accelerate insights, and maximize availability of information.
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
The document discusses the enterprise data hub (EDH) as a new approach for data management. The EDH allows organizations to bring applications to data rather than copying data to applications. It provides a full-fidelity active compliance archive, accelerates time to insights through scale, unlocks agility and innovation, consolidates data silos for a 360-degree view, and enables converged analytics. The EDH is implemented using open source, scalable, and cost-effective tools from Cloudera including Hadoop, Impala, and Cloudera Manager.
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis .
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis
This presentation provides an objective approach to make your legacy and custom-built applications agile and infused with intelligence. This allows your apps to utilize new and more substantial data sets as well as apply artificial intelligence and machine learning to take in-the-moment actions.
The document discusses how data accessibility is driving innovation in manufacturing through cloud and vault data management systems. It outlines how data has become more disruptive as information needs to be accessed in real-time across sites and stakeholders. Those not leveraging their data may fall behind. The presentation will demonstrate how a cloud-based vault provides real-time accessibility, analytics, and concurrent engineering across organizations and on mobile devices. Key benefits include data centricity, productivity, flexibility, and reduced costs compared to on-premise systems. Attendees will understand how partners can help leverage data for business optimization through these solutions.
The document discusses trends in data growth and computing. It notes that the amount of data being stored doubles every 18-24 months and provides examples of large data holdings from companies like AT&T, Google, and Walmart. It then summarizes key points about data growth from enterprises and digital lives. The rest of the document focuses on strategies and technologies for managing large and growing volumes of data, including parallel processing databases, new database architectures, and the QueryObject system.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization Denodo
Watch here: https://bit.ly/2NGQD7R
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But that scenario is rapidly changing with the increasing adoption of real-time data virtualization - a paradigm shift in the approach that organizations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes centre stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission-critical.
Attend this session to learn:
- Learn how you can meet cloud and data science challenges with data virtualization.
- Why data virtualization is increasingly finding enterprise-wide adoption
- Discover how customers are reducing costs and improving ROI with data virtualization
Future of Power: Power Strategy and Offerings for Denmark - Steve SibleyIBM Danmark
IBM is promoting its Power Systems as optimized for big data, analytics, mobile, social, and cloud workloads. Key highlights include Power Systems providing a flexible, secure infrastructure to support next generation applications and analytics on big data. IBM also emphasizes partnerships with software vendors and the open innovation through the OpenPOWER consortium to deliver client choice and drive down costs.
Data technology experts from Pivotal give the latest perspective on how big data analytics and applications are transforming organizations across industries.
This event provides an opportunity to learn about new developments in the rapidly-changing world of big data and understand best practices in creating Internet of Things (IoT) applications.
Learn more about the Pivotal Big Data Roadshow: http://pivotal.io/big-data/data-roadshow
Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...Cloudera, Inc.
PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers.
Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.
CL2015 - Datacenter and Cloud Strategy and PlanningCisco
This document discusses strategies for data center and cloud transformation over the next 5 years. It outlines key digital business trends like data growth, cloud adoption, and security threats that are driving organizations' IT initiatives. These include managing increased data and applications, optimizing cloud strategies, addressing disruptive business models, and securing distributed data and applications. The document advocates adopting flexible consumption models, automation, and supporting edge/IoT applications. It positions Cisco as uniquely able to enable digital transformations through its portfolio of networking, compute, storage, automation, analytics, and security solutions.
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
Simplifying Real-Time Architectures for IoT with Apache KuduCloudera, Inc.
3 Things to Learn About:
*Building scalable real time architectures for managing data from IoT
*Processing data in real time with components such as Kudu & Spark
*Customer case studies highlighting real-time IoT use cases
Similar to There are 250 Database products, are you running the right one? (20)
Are you interested in learning about creating an attractive website? Here it is! Take part in the challenge that will broaden your knowledge about creating cool websites! Don't miss this opportunity, only in "Redesign Challenge"!
this resume for sadika shaikh bca studentSadikaShaikh7
I am a dedicated BCA student with a strong foundation in web technologies, including PHP and MySQL. I have hands-on experience in Java and Python, and a solid understanding of data structures. My technical skills are complemented by my ability to learn quickly and adapt to new challenges in the ever-evolving field of computer science.
AI_dev Europe 2024 - From OpenAI to Opensource AIRaphaël Semeteys
Navigating Between Commercial Ownership and Collaborative Openness
This presentation explores the evolution of generative AI, highlighting the trajectories of various models such as GPT-4, and examining the dynamics between commercial interests and the ethics of open collaboration. We offer an in-depth analysis of the levels of openness of different language models, assessing various components and aspects, and exploring how the (de)centralization of computing power and technology could shape the future of AI research and development. Additionally, we explore concrete examples like LLaMA and its descendants, as well as other open and collaborative projects, which illustrate the diversity and creativity in the field, while navigating the complex waters of intellectual property and licensing.
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2023 and the first deals of 2024.
Hire a private investigator to get cell phone recordsHackersList
Learn what private investigators can legally do to obtain cell phone records and track phones, plus ethical considerations and alternatives for addressing privacy concerns.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
An invited talk given by Mark Billinghurst on Research Directions for Cross Reality Interfaces. This was given on July 2nd 2024 as part of the 2024 Summer School on Cross Reality in Hagenberg, Austria (July 1st - 7th)
Coordinate Systems in FME 101 - Webinar SlidesSafe Software
If you’ve ever had to analyze a map or GPS data, chances are you’ve encountered and even worked with coordinate systems. As historical data continually updates through GPS, understanding coordinate systems is increasingly crucial. However, not everyone knows why they exist or how to effectively use them for data-driven insights.
During this webinar, you’ll learn exactly what coordinate systems are and how you can use FME to maintain and transform your data’s coordinate systems in an easy-to-digest way, accurately representing the geographical space that it exists within. During this webinar, you will have the chance to:
- Enhance Your Understanding: Gain a clear overview of what coordinate systems are and their value
- Learn Practical Applications: Why we need datams and projections, plus units between coordinate systems
- Maximize with FME: Understand how FME handles coordinate systems, including a brief summary of the 3 main reprojectors
- Custom Coordinate Systems: Learn how to work with FME and coordinate systems beyond what is natively supported
- Look Ahead: Gain insights into where FME is headed with coordinate systems in the future
Don’t miss the opportunity to improve the value you receive from your coordinate system data, ultimately allowing you to streamline your data analysis and maximize your time. See you there!
Data Protection in a Connected World: Sovereignty and Cyber Securityanupriti
Delve into the critical intersection of data sovereignty and cyber security in this presentation. Explore unconventional cyber threat vectors and strategies to safeguard data integrity and sovereignty in an increasingly interconnected world. Gain insights into emerging threats and proactive defense measures essential for modern digital ecosystems.
How RPA Help in the Transportation and Logistics Industry.pptxSynapseIndia
Revolutionize your transportation processes with our cutting-edge RPA software. Automate repetitive tasks, reduce costs, and enhance efficiency in the logistics sector with our advanced solutions.
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.
Interaction Latency: Square's User-Centric Mobile Performance MetricScyllaDB
Mobile performance metrics often take inspiration from the backend world and measure resource usage (CPU usage, memory usage, etc) and workload durations (how long a piece of code takes to run).
However, mobile apps are used by humans and the app performance directly impacts their experience, so we should primarily track user-centric mobile performance metrics. Following the lead of tech giants, the mobile industry at large is now adopting the tracking of app launch time and smoothness (jank during motion).
At Square, our customers spend most of their time in the app long after it's launched, and they don't scroll much, so app launch time and smoothness aren't critical metrics. What should we track instead?
This talk will introduce you to Interaction Latency, a user-centric mobile performance metric inspired from the Web Vital metric Interaction to Next Paint"" (web.dev/inp). We'll go over why apps need to track this, how to properly implement its tracking (it's tricky!), how to aggregate this metric and what thresholds you should target.
9. Data management
• Growing data volume
• Need for real-time information
• Security concerns
• Growing complexity of systems
• Increased HA requirements
• Underutilized servers and
storage
• Drive toward enhanced SLAs
Distributed data management
• Integration issues
• Administration
• Data duplication
• Security concerns
• Performance and scalability
• Synchronizing repositories
• Content, unstructured data
Data management pain points intensify . . .