Daum evaluated solutions that could address the limitations in the resource-intensive analysis required by Hadoop and the NoSQL database management systems. To meet the data analysis requirements for its search engine and the Internet services businesses, the company selected Pivotal Greenplum Database, which connects to Hadoop and enables the co-processing of both structured and unstructured data within a single solution.
To learn more, visit pivotal.io/big-data/pivotal-greenplum-database.
As more organizations look to Hadoop as the technology solution for big data analytics, common questions arise.
Join us in this case study look at an online services provider's experience with Big Data and how they answered the questions:
*What does big data analytics do that my existing BI software doesn’t?
*Will Hadoop replace my data warehouse?
*What about Hive?
Complement Your Existing Data Warehouse with Big Data & HadoopDatameer
To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html
With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging.
Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis.
Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to:
-Get all the data your business needs quickly into one environment
Shorten the time to insight from months to days
Extend the life of your existing data warehouse investments
Enable your business analysts to ask and answer bigger questions
This was presented at NHN on Jan. 27, 2009.
It introduces Big Data, its storages, and its analyses.
Especially, it covers MapReduce debates and hybrid systems of RDBMS and MapReduce.
In addition, in terms of Schema-Free, various non-relational data storages are explained.
How to select a modern data warehouse and get the most out of it?Slim Baltagi
In the first part of this talk, we will give a setup and definition of modern cloud data warehouses as well as outline problems with legacy and on-premise data warehouses.
We will speak to selecting, technically justifying, and practically using modern data warehouses, including criteria for how to pick a cloud data warehouse and where to start, how to use it in an optimum way and use it cost effectively.
In the second part of this talk, we discuss the challenges and where people are not getting their investment. In this business-focused track, we cover how to get business engagement, identifying the business cases/use cases, and how to leverage data as a service and consumption models.
Pervasive analytics through data & analytic centricityCloudera, Inc.
Cloudera and Teradata discuss the best-in-class solution enabling companies to put data and analytics at the center of their strategy, achieve the highest forms of agility, while reducing the costs and complexity of their current environment.
As more organizations look to Hadoop as the technology solution for big data analytics, common questions arise.
Join us in this case study look at an online services provider's experience with Big Data and how they answered the questions:
*What does big data analytics do that my existing BI software doesn’t?
*Will Hadoop replace my data warehouse?
*What about Hive?
Complement Your Existing Data Warehouse with Big Data & HadoopDatameer
To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html
With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging.
Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis.
Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to:
-Get all the data your business needs quickly into one environment
Shorten the time to insight from months to days
Extend the life of your existing data warehouse investments
Enable your business analysts to ask and answer bigger questions
This was presented at NHN on Jan. 27, 2009.
It introduces Big Data, its storages, and its analyses.
Especially, it covers MapReduce debates and hybrid systems of RDBMS and MapReduce.
In addition, in terms of Schema-Free, various non-relational data storages are explained.
How to select a modern data warehouse and get the most out of it?Slim Baltagi
In the first part of this talk, we will give a setup and definition of modern cloud data warehouses as well as outline problems with legacy and on-premise data warehouses.
We will speak to selecting, technically justifying, and practically using modern data warehouses, including criteria for how to pick a cloud data warehouse and where to start, how to use it in an optimum way and use it cost effectively.
In the second part of this talk, we discuss the challenges and where people are not getting their investment. In this business-focused track, we cover how to get business engagement, identifying the business cases/use cases, and how to leverage data as a service and consumption models.
Pervasive analytics through data & analytic centricityCloudera, Inc.
Cloudera and Teradata discuss the best-in-class solution enabling companies to put data and analytics at the center of their strategy, achieve the highest forms of agility, while reducing the costs and complexity of their current environment.
Better Together: The New Data Management OrchestraCloudera, Inc.
To ingest, store, process and leverage big data for maximum business impact requires integrating systems, processing frameworks, and analytic deployment options. Learn how Cloudera’s enterprise data hub framework, MongoDB, and Teradata Data Warehouse working in concert can enable companies to explore data in new ways and solve problems that not long ago might have seemed impossible.
Gone are the days of NoSQL and SQL competing for center stage. Visionary companies are driving data subsystems to operate in harmony. So what’s changed?
In this webinar, you will hear from executives at Cloudera, Teradata and MongoDB about the following:
How to deploy the right mix of tools and technology to become a data-driven organization
Examples of three major data management systems working together
Real world examples of how business and IT are benefiting from the sum of the parts
Join industry leaders Charles Zedlewski, Chris Twogood and Kelly Stirman for this unique panel discussion, moderated by BI Research analyst, Colin White.
Cisco Big Data Warehouse Expansion Featuring MapR DistributionAppfluent Technology
Learn more about the Cisco Big Data Warehouse Expansion Solution featuring MapR Distribution including Apache Hadoop.
The BDWE solution begins with the collection of data usage statistics by Appfluent. Then the BDWE solution optimizes Cisco UCS hardware for running the MapR Distribution including Hadoop, software for federating multiple data sources, and a comprehensive services methodology for assessing, migrating, virtualizing, and operating a logically expanded warehouse.
Are you exploring the transition to becoming a cloud broker? Establishing cloud business practices and marketing is one of the most overlooked areas by enterprise IT professionals. This session explores the role marketing and the 4 Ps - Product, Price, Promotion, and Placement - play in multi-cloud and cloud brokerage. Don’t let your technical success die on the vine without exposure!aka the 4 Ps of Multi-cloud
Hadoop World 2011: I Want to Be BIG - Lessons Learned at Scale - David "Sunny...Cloudera, Inc.
SGI has been a leading commercial vendor of Hadoop clusters since 2008. Leveraging SGI's experience with high performance clusters at scale, SGI has delivered individual Hadoop clusters of up to 4000 nodes. Integration, performance, and management all become issues at scale, and Hadoop clusters scale! In this presentation, SGI will discuss representative customer use cases, major design considerations for performance and power optimization, how integrated Hadoop solutions leveraging CDH, SGI Rackable clusters, and SGI Management Center best meet customer needs, and how SGI envisions the needs of enterprise customers evolving as Hadoop continues to move into mainstream adoption.
Modern Data Architecture: In-Memory with Hadoop - the new BIKognitio
Is Hadoop ready for high-concurrency complex BI and Advanced Analytics? Roaring performance and fast, low-latency execution is possible when an in-memory analytical platform is paired with the Apache Hadoop framework. Join Hortonworks and Kognitio for an informative Web Briefing on putting Hadoop at the center of your modern data architecture—with zero disruption to business users.
Asterix Solution’s Hadoop Training is designed to help applications scale up from single servers to thousands of machines. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
http://www.asterixsolution.com/big-data-hadoop-training-in-mumbai.html
Duration - 25 hrs
Session - 2 per week
Live Case Studies - 6
Students - 16 per batch
Venue - Thane
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...NoSQLmatters
Come to this deep dive on how Pivotal's Data Lake Vision is evolving by embracing next generation in-memory data exchange and compute technologies around Spark and Tachyon. Did we say Hadoop, SQL, and what's the shortest path to get from past to future state? The next generation of data lake technology will leverage the availability of in-memory processing, with an architecture that supports multiple data analytics workloads within a single environment: SQL, R, Spark, batch and transactional.
Better Together: The New Data Management OrchestraCloudera, Inc.
To ingest, store, process and leverage big data for maximum business impact requires integrating systems, processing frameworks, and analytic deployment options. Learn how Cloudera’s enterprise data hub framework, MongoDB, and Teradata Data Warehouse working in concert can enable companies to explore data in new ways and solve problems that not long ago might have seemed impossible.
Gone are the days of NoSQL and SQL competing for center stage. Visionary companies are driving data subsystems to operate in harmony. So what’s changed?
In this webinar, you will hear from executives at Cloudera, Teradata and MongoDB about the following:
How to deploy the right mix of tools and technology to become a data-driven organization
Examples of three major data management systems working together
Real world examples of how business and IT are benefiting from the sum of the parts
Join industry leaders Charles Zedlewski, Chris Twogood and Kelly Stirman for this unique panel discussion, moderated by BI Research analyst, Colin White.
Cisco Big Data Warehouse Expansion Featuring MapR DistributionAppfluent Technology
Learn more about the Cisco Big Data Warehouse Expansion Solution featuring MapR Distribution including Apache Hadoop.
The BDWE solution begins with the collection of data usage statistics by Appfluent. Then the BDWE solution optimizes Cisco UCS hardware for running the MapR Distribution including Hadoop, software for federating multiple data sources, and a comprehensive services methodology for assessing, migrating, virtualizing, and operating a logically expanded warehouse.
Are you exploring the transition to becoming a cloud broker? Establishing cloud business practices and marketing is one of the most overlooked areas by enterprise IT professionals. This session explores the role marketing and the 4 Ps - Product, Price, Promotion, and Placement - play in multi-cloud and cloud brokerage. Don’t let your technical success die on the vine without exposure!aka the 4 Ps of Multi-cloud
Hadoop World 2011: I Want to Be BIG - Lessons Learned at Scale - David "Sunny...Cloudera, Inc.
SGI has been a leading commercial vendor of Hadoop clusters since 2008. Leveraging SGI's experience with high performance clusters at scale, SGI has delivered individual Hadoop clusters of up to 4000 nodes. Integration, performance, and management all become issues at scale, and Hadoop clusters scale! In this presentation, SGI will discuss representative customer use cases, major design considerations for performance and power optimization, how integrated Hadoop solutions leveraging CDH, SGI Rackable clusters, and SGI Management Center best meet customer needs, and how SGI envisions the needs of enterprise customers evolving as Hadoop continues to move into mainstream adoption.
Modern Data Architecture: In-Memory with Hadoop - the new BIKognitio
Is Hadoop ready for high-concurrency complex BI and Advanced Analytics? Roaring performance and fast, low-latency execution is possible when an in-memory analytical platform is paired with the Apache Hadoop framework. Join Hortonworks and Kognitio for an informative Web Briefing on putting Hadoop at the center of your modern data architecture—with zero disruption to business users.
Asterix Solution’s Hadoop Training is designed to help applications scale up from single servers to thousands of machines. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
http://www.asterixsolution.com/big-data-hadoop-training-in-mumbai.html
Duration - 25 hrs
Session - 2 per week
Live Case Studies - 6
Students - 16 per batch
Venue - Thane
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...NoSQLmatters
Come to this deep dive on how Pivotal's Data Lake Vision is evolving by embracing next generation in-memory data exchange and compute technologies around Spark and Tachyon. Did we say Hadoop, SQL, and what's the shortest path to get from past to future state? The next generation of data lake technology will leverage the availability of in-memory processing, with an architecture that supports multiple data analytics workloads within a single environment: SQL, R, Spark, batch and transactional.
Kyria prides itself on building excellent relationships with all of their customers and suppliers. As a national supplier to over 50 active accounts and 200 doors, Kyria’s customers include major department stores, ready-to-wear stores, gift shops and independent specialty boutiques.
Graphene Position Paper (E-Nano Newsletter Special Issue)Phantoms Foundation
This E-nano Newsletter special issue contains the final version of the nanoICT position paper on Graphene (one-atom-thick sheet of carbon / in 2010, A.K. Geim
and K. Novoselov, were awarded the Nobel Prize in physics for “groundbreaking experiments regarding the two-dimensional material graphene”) summarising the
current state of progress and open perspectives concerning the emergence of graphene-based technologies and applications. This paper is a mixture between a short review of recent achievements and ingredients for the elaboration of a more specific and detailed roadmap.
Big Data" šodien ir viens no populārākajiem mārketinga saukļiem, kas tiek pamatoti un nepamatoti izmantots, runājot par (lielu?) datu uzglabāšanu un apstrādi. Prezentācijā es aplūkošu, kas tad patiesībā ir "big data" no tehnoloģijju viedokļa, kādi ir galvenie izmantošanas scenāriji un ieguvumi. Prezentācijā apskatīšu tādas tehnoloģijas kā Hadoop, HDFS, MapReduce, Impala, Sparc, Pig, Hive un citas. Tāpat tiks apskatīta integrācija ar tradicionālām DBVS un galvenie izmantošanas scenāriji.
This is everything I (Andy Clark from Shine Training) learned from the past 7 weeks of trying lots of new ideas to help me get in shape. Many thanks to Tim Ferriss for writing a great book!
Case Study - DataXu Uses Qubole To Make Big Data Cloud Querying, Highly Avail...Vasu S
DataXu uses Qubole Data Platform to automate and manage on-premise deployments, provision clusters, maintain Hadoop distributions, and upkeep Adhoc clusters with Qubole's Hive as a service.
https://www.qubole.com/resources/case-study/dataxu
Big Data Made Easy: A Simple, Scalable Solution for Getting Started with HadoopPrecisely
With so many new, evolving frameworks, tools, and languages, a new big data project can lead to confusion and unwarranted risk.
Many organizations have found Data Warehouse Optimization with Hadoop to be a good starting point on their Big Data journey. Offloading ETL workloads from the enterprise data warehouse (EDW) into Hadoop is a well-defined use case that produces tangible results for driving more insights while lowering costs. You gain significant business agility, avoid costly EDW upgrades, and free up EDW capacity for faster queries. This quick win builds credibility and generates savings to reinvest in more Big Data projects.
A proven reference architecture that includes everything you need in a turnkey solution – the Hadoop distribution, data integration software, servers, networking and services – makes it even easier to get started.
This new solution from Capgemini, implemented in
partnership with Informatica, Cloudera and Appfluent,
optimizes the ratio between the value of data and storage
costs, making it easy to take advantage of new big data
technologies.
Modern apps and services are leveraging data to change the way we engage with users in a more personalized way. Skyla Loomis talks big data, analytics, NoSQL, SQL and how IBM Cloud is open for data.
Learn more by visiting our Bluemix Hybrid page: http://ibm.co/1PKN23h
IBM® dashDB™ is a fast, fully managed, cloud data warehouse that utilizes integrated analytics to rapidly deliver answers. dashDB’s unique in-database analytics, R predictive modeling and business intelligence tools free you to analyze your data and get precise insights, quicker. dashDB is simple to get up and running with rapid provisioning in IBM Bluemix™. You can test the solution or start using dashDB for no charge, for up to one gigabyte of data and then just $50 US
per month for 20 gigabytes of data storage. Larger instance sizes with multi-terabyte capacity are available as you grow your data, and as your users require a dedicated environment. Massively Parallel Processing (MPP) enables even faster query speeds as well as larger scale data sets.
Data lakes are central repositories that store large volumes of structured, unstructured, and semi-structured data. They are ideal for machine learning use cases and support SQL-based access and programmatic distributed data processing frameworks. Data lakes can store data in the same format as its source systems or transform it before storing it. They support native streaming and are best suited for storing raw data without an intended use case. Data quality and governance practices are crucial to avoid a data swamp. Data lakes enable end-users to leverage insights for improved business performance and enable advanced analytics.
Hadoop in 2015: Keys to Achieving Operational Excellence for the Real-Time En...MapR Technologies
In this webinar, Carl W. Olofson, Research Vice President, Application Development and Deployment for IDC, and Dale Kim, Director of Industry Solutions for MapR, will provide an insightful outlook for Hadoop in 2015, and will outline why enterprises should consider using Hadoop as a "Decision Data Platform" and how it can function as a single platform for both online transaction processing (OLTP) and real-time analytics.
GCP On Prem Buyers Guide - White-paper | Qubole Vasu S
A buyer's guide for migrating a data lake to google cloud, we look at the efficiency and agility an organization can achieve by adopting the qubole open data lake platform & google cloud platform
https://www.qubole.com/resources/white-papers/gcp-on-prem-buyers-guide
2020 Cloud Data Lake Platforms Buyers Guide - White paper | QuboleVasu S
Qubole's buyer guide about how cloud data lake platform helps organizations to achieve efficiency & agility by adopting an open data lake platform and why data lakes are moving to the cloud
https://www.qubole.com/resources/white-papers/2020-cloud-data-lake-platforms-buyers-guide
Hadoop and the Data Warehouse: When to Use Which DataWorks Summit
In recent years, Apache™ Hadoop® has emerged from humble beginnings to disrupt the traditional disciplines of information management. As with all technology innovation, hype is rampant, and data professionals are easily overwhelmed by diverse opinions and confusing messages.
Even seasoned practitioners sometimes miss the point, claiming for example that Hadoop replaces relational databases and is becoming the new data warehouse. It is easy to see where these claims originate since both Hadoop and Teradata® systems run in parallel, scale up to enormous data volumes and have shared-nothing architectures. At a conceptual level, it is easy to think they are interchangeable, but the differences overwhelm the similarities. This session will shed light on the differences and help architects, engineering executives, and data scientists identify when to deploy Hadoop and when it is best to use MPP relational database in a data warehouse, discovery platform, or other workload-specific applications.
Two of the most trusted experts in their fields, Steve Wooledge, VP of Product Marketing from Teradata and Jim Walker of Hortonworks will examine how big data technologies are being used today by practical big data practitioners.
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
The Tanzu Developer Connect is a hands-on workshop that dives deep into TAP. Attendees receive a hands on experience. This is a great program to leverage accounts with current TAP opportunities.
The Tanzu Developer Connect is a hands-on workshop that dives deep into TAP. Attendees receive a hands on experience. This is a great program to leverage accounts with current TAP opportunities.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Daum Communications Case Study
1. DAUM COMMUNICATIONS
Using big data analytics to understand and predict
user behavior
ESSENTIALS
Industry
Telecommunications
Company Size
2,000+ employees
Business Challenges
• Reduced responsiveness due to
inability to perform realtime
analysis
• Increased complexity from NoSQL
database management systems
• Reliance on resource-intensive
data analysis
• Reduced capability to make ad-
hoc queries on unstructured data
Solution
• EMC VNX unified storage
• Pivotal Greenplum Database
OVERVIEW
Daum Communications (Daum) is one of the leading providers of Korean-language
online services, including the news and information portal Daum.net, web-based email
service Hanmail.net, and the Daum Cafe online community. Headquartered in Jeju
Island, the company provides mobile web services, search marketing, and electronic
mapping. It also sells online advertising products through Daum.net. Daum is the
second largest web portal service provider in terms of daily visits in Korea and has
operating centers in Seoul and on Jeju Island.
Through its extensive range of Internet services and sale of online advertising
products, Daum generates vast amounts of unstructured data. The company has one
of the largest Apache Hadoop clusters in Korea, and analyzes its data to gain critical
competitive information in a number of areas, including user preferences and
behavior, search rankings, and advertisement targeting.
COMPLEX ENVIRONMENT IMPEDES DATA ANALYSIS
Facing intense domestic and global competition from a number of search engines that
are growing market share across desktop and mobile searches, Daum’s businesses
needed to make faster and better decisions to protect the company’s 20 percent share
of the Korean search market.
The company needed to analyze and make immediate decisions on its vast data stores
by extracting knowledge from its data in real time. But Daum was more interested in
solving analytic problems than in exploring relationships between data that are
available in traditional relational database systems. As a result, Daum was using
Hadoop to store data, and was using NoSQL non-relational database management
systems such as Cassandra and Storm as the Hadoop Distributed File System (HDFS)
to provide greater speed in performing Big Data analytics on unstructured data. This
solution landscape presented the company with serious challenges.
“Performing ad-hoc and multidimensional queries and analysis through Hadoop on our
unstructured data proved difficult,” says Jun-Sik Eom, Team Manager, Data
Technology Department, Daum Communications. “We were restricted in the speed of
data analysis due the batch processing of both unstructured and structured data,
which meant we relied heavily on the capability of our developers. Data analysis of
complex forms was also challenging in the NoSQL database.”
Because Daum’s data must be constantly reviewed, the company sought a solution
that would enable employees to perform high-speed queries on the data residing in
Hadoop. Additionally, Daum wanted to improve access through tools that were already
familiar to developers and database administrators.
CUSTOMER PROFILE
2. Benefits
• Increased data loading and
processing speeds
• Improved accuracy in generating
search results and predicting user
behaviour
• Increased efficiency by
performing rapid queries on the
data
• Reduced expenditures through
improved scalability
PIVOTAL GREENPLUM DATABASE ENABLES HIGH-SPEED
ANALYSIS OF UNSTRUCTURED DATA
Daum evaluated solutions that could address the limitations in the resource-intensive
analysis required by Hadoop and the NoSQL database management systems. To meet
the data analysis requirements for its search engine and Internet services businesses,
the company selected Pivotal Greenplum Database, which connects to Hadoop and
enables the co-processing of both structured and unstructured data within a single
solution.
“We were attracted to Pivotal Greenplum Database because of the advantage it had in
mixing the merits of database, data warehouse, and business intelligence,” says Eom.
“We can now use a single platform to run high-speed analytic queries on our most
appropriate data stores.”
“We were attracted to Pivotal Greenplum Database because of the
advantage it had in mixing the merits of database, data
warehouse, and business intelligence. We can now use a single
platform to run high-speed analytic queries on our most
appropriate data stores.”
Jun-Sik Eom,
Team Manager, Data Technology Department, Daum Communications
DELIVERING NEW BUSINESS INSIGHTS FROM REALTIME
ANALYSIS
To support its efforts to gain market share, Daum is using Pivotal Greenplum Database
to provide improved services and search accuracy to its users. Through realtime data
gathering and analysis of Internet searches and user behavior within its various online
services, the company can better predict future behavior and demand.
Daum can now make multiple queries—both in real time and over time as user patterns
and knowledge emerge—due to massively parallel processing (MPP) architecture, which
enables fast data loading and high-speed queries on the data. In addition to performing
real-time weblog analysis, the company can re-analyze data that has already been
processed and gain meaningful results with these various interpretations. Pivotal
helped Daum achieve an increased depth of knowledge, which is just as critical as
breadth in terms of delivering services.
ELIMINATING ROADBLOCKS TO SPEEDY QUERYING
Performing ad-hoc queries on the data stored in NoSQL databases from the Pivotal
Greenplum Database means administrators can use familiar SQL commands to perform
massive and multidimensional analysis. This reduces the company’s reliance on finding
specialist NoSQL and Hadoop skill sets, and minimizes the workload for employees.
“One of the most important elements in effectively using Big Data is securing the right
people,” says Eom. “We used to struggle with having the resources needed to perform
queries, which greatly reduced our processing efficiency. Today, instead of performing
queries on the NoSQL systems, we collect the data residing in Hadoop and NoSQL, and
then save it in Pivotal Greenplum Database to execute the analysis.”