Momentum provides easy to use platform for processing large volume of data streams in realtime. This is an ideal solution for IoT and click stream analytics
Delivered this talk as part of Spark & Kafka Summit 2017 organized by Unicom Learning Conference.
Big data processing is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution and introduction of new ideas. Apache Spark is at the cusp of overtaking MapReduce to emerge as the de-facto standard for big data processing. Thanks to its multi-functional capabilities (SQL, Structured Streaming, ML Pipelines and GraphX) under one unified platform , Spark is now a dominant compute technology across various industry use cases and real-time analytics applications. Apache Spark in past few years has seen successful production and commercial deployments across E-Commerce, Healthcare and Travel industry.
Session gave audience an understanding about the latest and upcoming trends in Big-Data Analytics and the role of Spark in enabling those future use-cases of advanced analytics.
Session explored the latest concepts from Apache Spark 2.x and introduction to various ML/DL frameworks that can run Spark along with some real-life use-cases and applications from Retail and IoT verticals.
How are new IoT devices being designed, built & integrated to big data platforms such as Hadoop. Ammeon design such systems to integrate with and provide critical support for new device creators to bring their products to market.
Powering the Internet of Things with Apache HadoopCloudera, Inc.
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Operational information processing: lightning-fast, delightfully simpleXylos
How can you as an industrial company or service provider collect and analyse data from your operational production equipment in a simple, fast and smart way? During this session, HPE gives you some practical examples – and what’s more, you’ll discover the underlying reference architecture. As a result, you’ll boost the efficiency of your production process and tune the services you provide to the needs of your customers.
2016 Cybersecurity Analytics State of the UnionCloudera, Inc.
3 Things to Learn About:
-Ponemon Institute's 2016 big data cybersecurity analytics research report
-Quantifiable returns organizations are seeing with big data cybersecurity analytics
-Trends in the industry that are affecting cybersecurity strategies
Delivered this talk as part of Spark & Kafka Summit 2017 organized by Unicom Learning Conference.
Big data processing is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution and introduction of new ideas. Apache Spark is at the cusp of overtaking MapReduce to emerge as the de-facto standard for big data processing. Thanks to its multi-functional capabilities (SQL, Structured Streaming, ML Pipelines and GraphX) under one unified platform , Spark is now a dominant compute technology across various industry use cases and real-time analytics applications. Apache Spark in past few years has seen successful production and commercial deployments across E-Commerce, Healthcare and Travel industry.
Session gave audience an understanding about the latest and upcoming trends in Big-Data Analytics and the role of Spark in enabling those future use-cases of advanced analytics.
Session explored the latest concepts from Apache Spark 2.x and introduction to various ML/DL frameworks that can run Spark along with some real-life use-cases and applications from Retail and IoT verticals.
How are new IoT devices being designed, built & integrated to big data platforms such as Hadoop. Ammeon design such systems to integrate with and provide critical support for new device creators to bring their products to market.
Powering the Internet of Things with Apache HadoopCloudera, Inc.
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Operational information processing: lightning-fast, delightfully simpleXylos
How can you as an industrial company or service provider collect and analyse data from your operational production equipment in a simple, fast and smart way? During this session, HPE gives you some practical examples – and what’s more, you’ll discover the underlying reference architecture. As a result, you’ll boost the efficiency of your production process and tune the services you provide to the needs of your customers.
2016 Cybersecurity Analytics State of the UnionCloudera, Inc.
3 Things to Learn About:
-Ponemon Institute's 2016 big data cybersecurity analytics research report
-Quantifiable returns organizations are seeing with big data cybersecurity analytics
-Trends in the industry that are affecting cybersecurity strategies
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/07/the-data-driven-engineering-revolution-a-presentation-from-edge-impulse/
Zach Shelby, Co-founder and CEO of Edge Impulse, presents the “Data-Driven Engineering Revolution” tutorial at the May 2021 Embedded Vision Summit.
In this talk, IoT industry pioneer and Edge Impulse co-founder Zach Shelby shares insights about how machine learning is revolutionizing embedded engineering. Advances in silicon and deep learning are enabling embedded machine learning (TinyML) to be deployed where data is born, from industrial sensor data to audio and video.
Shelby explains the new paradigm of data-driven engineering with ML, showing how developers are using data instead of code to drive algorithm innovation. To support widespread deployment, ML workloads need to run on embedded computing targets from MCUs to GPUs, with MLOps processes to support efficient development and deployment. Industrial, logistics and health markets are particularly ripe to deploy this data-driven approach, and Shelby highlights several exciting case studies.
Building a Modern FinTech Big Data InfrastructureDatabricks
The cloud is now the first choice for large-scale analytics, but organizations that have sunk investment into Hadoop on-premises are also challenged with maintaining operations. This can make a move to modern analytics platforms like Spark difficult or impossible. Learn about innovations for large-scale migration that can take full advantage of cloud-based analytics without disrupting operations.
DATA @ NFLX (Tableau Conference 2014 Presentation)Blake Irvine
I presented this at a 2014 Tableau Conference session with Albert Wong.
Netflix relies on data to make decisions ranging from buying and recommending content, to improving the streaming experience on devices.
This presentation shares our Big Data analytics architecture and the tools used to make data accessible throughout our business, focusing on how Tableau fits into our organization and why it aligns well with our culture.
Using The Internet of Things for Population Health Management - StampedeCon 2016StampedeCon
The Internet of (Human) Things is just beginning to take shape. The human body is an inexhaustible source of data about personal health, and the healthcare industry is just beginning to scratch the surface of the potential insights and value that will come from that data. While much of healthcare traditionally focuses on the episodic delivery of services, the Affordable Care Act is pushing healthcare providers, payers, and self-funded employer groups to look at ways to proactively encourage healthy behaviors. Providing personal health devices as a way to promote individual health is one way that healthcare is beginning to take advantage of IoT technologies. This session provides insight into how IoT is being leveraged in population health management through a solution jointly delivered by Amitech Solutions and Big Cloud Analytics. Attendees will learn how Hadoop is being used to gather personal device from various vendors, integrate and analyze that information, differentiate trends across regional and cultural diversity, and provide personal recommendations and insights into health risks. This session presents one important way the healthcare industry is leveraging IoT.
This talk was held at the 13th meeting on Sept 23rd 2014 by Bruno Ungermann.
Conceptual overview of Hadoop based analytics, comparison between data warehouse architecture and Big Data architecture, characteristics of „schema on read“, typical Big Data use cases like customer analytics, operational analytics and EDW optimization, short software demo
Modern IoT operations can drive digital transformation by analyzing the unprecedented amounts of data generated from devices and sensors in real-time.
Apache Spark is a widely used stream processing engine for real-time IoT applications. Spark streaming offers a rich set of APIs in the areas of ingestion, cloud integration, multi-source joins, blending streams with static data, time-window aggregations, transformations, data cleansing, and strong support for machine learning and predictive analytics.
Join Anand Venugopal, AVP & Business Head, StreamAnalytix and Sameer Bhide, Senior Solutions Architect, StreamAnalytix to learn about the rapid development and operationalization of real-time IoT applications covering an end-to-end flow of ingest, insight, action, and feedback.
The webinar will cover the following:
Generic IoT application blueprint
Case studies on IoT applications built on Apache Spark – connected car and industrial IoT
Demonstration of an easy, visual approach to building IoT Spark apps
Real-Time Analytics with Apache Cassandra and Apache SparkGuido Schmutz
Time series data is everywhere: IoT, sensor data, financial transactions. The industry has moved to databases like Cassandra to handle the high velocity and high volume of data that is now common place. However data is pointless without being able to process it in near real time. That's where Spark combined with Cassandra comes in! What was one just your storage system (Cassandra) can be transformed into an analytics system and it's really surprising how easy it is!
An overview of how MongoDB and Apache Spark are enabling IoT innovators to create new business models.
Presented at the Business of IoT meetup in London on Jan 13th 2016
Webinar: Rearchitecting Storage for the Next Wave of Splunk Data GrowthStorage Switzerland
Join Storage Switzerland and SwiftStack, a Splunk technology partner, for our webinar where our panel of experts will discuss the value of having Splunk analyze larger datasets while providing insight into overcoming infrastructure cost and complexity challenges through Splunk enhancements like SmartStore.
IoT Suite is an enterprise grade solution that allows you to get started quickly through a set of extensible pre-configured solutions for common IoT scenarios
How a Media Data Platform Drives Real-time Insights & Analytics using Apache ...Databricks
Roularta is a leading publishing company in Belgium. As digital news and channels move at a rapid pace and contain massive volumes of data, Roularta decided in 2019 to invest in a Spark-based data platform to drive true real-time website analytics and unlock insights on previously untouched (big) data sources. In this talk we’ll first explain why and how Roularta embarked from a classical data warehouse to a Spark-based Lakehouse using Delta. We’ll outline the series of publishing & marketing use-cases done in the last 12 months and highlight for each use-case the advantages of Spark and how the team further tuned performance to truly deliver insights with high velocity.
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager...Dataconomy Media
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager at HPE, presented "Using advanced analytics functions of HPE Vertica for the following use cases: IoT, clickstream, machine data, integration with Hadoop & Kafka …" as part of the Big Data, Budapest v 3.0 meetup organised on the 19th of May 2016 at Skyscanner's headquarters.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/07/the-data-driven-engineering-revolution-a-presentation-from-edge-impulse/
Zach Shelby, Co-founder and CEO of Edge Impulse, presents the “Data-Driven Engineering Revolution” tutorial at the May 2021 Embedded Vision Summit.
In this talk, IoT industry pioneer and Edge Impulse co-founder Zach Shelby shares insights about how machine learning is revolutionizing embedded engineering. Advances in silicon and deep learning are enabling embedded machine learning (TinyML) to be deployed where data is born, from industrial sensor data to audio and video.
Shelby explains the new paradigm of data-driven engineering with ML, showing how developers are using data instead of code to drive algorithm innovation. To support widespread deployment, ML workloads need to run on embedded computing targets from MCUs to GPUs, with MLOps processes to support efficient development and deployment. Industrial, logistics and health markets are particularly ripe to deploy this data-driven approach, and Shelby highlights several exciting case studies.
Building a Modern FinTech Big Data InfrastructureDatabricks
The cloud is now the first choice for large-scale analytics, but organizations that have sunk investment into Hadoop on-premises are also challenged with maintaining operations. This can make a move to modern analytics platforms like Spark difficult or impossible. Learn about innovations for large-scale migration that can take full advantage of cloud-based analytics without disrupting operations.
DATA @ NFLX (Tableau Conference 2014 Presentation)Blake Irvine
I presented this at a 2014 Tableau Conference session with Albert Wong.
Netflix relies on data to make decisions ranging from buying and recommending content, to improving the streaming experience on devices.
This presentation shares our Big Data analytics architecture and the tools used to make data accessible throughout our business, focusing on how Tableau fits into our organization and why it aligns well with our culture.
Using The Internet of Things for Population Health Management - StampedeCon 2016StampedeCon
The Internet of (Human) Things is just beginning to take shape. The human body is an inexhaustible source of data about personal health, and the healthcare industry is just beginning to scratch the surface of the potential insights and value that will come from that data. While much of healthcare traditionally focuses on the episodic delivery of services, the Affordable Care Act is pushing healthcare providers, payers, and self-funded employer groups to look at ways to proactively encourage healthy behaviors. Providing personal health devices as a way to promote individual health is one way that healthcare is beginning to take advantage of IoT technologies. This session provides insight into how IoT is being leveraged in population health management through a solution jointly delivered by Amitech Solutions and Big Cloud Analytics. Attendees will learn how Hadoop is being used to gather personal device from various vendors, integrate and analyze that information, differentiate trends across regional and cultural diversity, and provide personal recommendations and insights into health risks. This session presents one important way the healthcare industry is leveraging IoT.
This talk was held at the 13th meeting on Sept 23rd 2014 by Bruno Ungermann.
Conceptual overview of Hadoop based analytics, comparison between data warehouse architecture and Big Data architecture, characteristics of „schema on read“, typical Big Data use cases like customer analytics, operational analytics and EDW optimization, short software demo
Modern IoT operations can drive digital transformation by analyzing the unprecedented amounts of data generated from devices and sensors in real-time.
Apache Spark is a widely used stream processing engine for real-time IoT applications. Spark streaming offers a rich set of APIs in the areas of ingestion, cloud integration, multi-source joins, blending streams with static data, time-window aggregations, transformations, data cleansing, and strong support for machine learning and predictive analytics.
Join Anand Venugopal, AVP & Business Head, StreamAnalytix and Sameer Bhide, Senior Solutions Architect, StreamAnalytix to learn about the rapid development and operationalization of real-time IoT applications covering an end-to-end flow of ingest, insight, action, and feedback.
The webinar will cover the following:
Generic IoT application blueprint
Case studies on IoT applications built on Apache Spark – connected car and industrial IoT
Demonstration of an easy, visual approach to building IoT Spark apps
Real-Time Analytics with Apache Cassandra and Apache SparkGuido Schmutz
Time series data is everywhere: IoT, sensor data, financial transactions. The industry has moved to databases like Cassandra to handle the high velocity and high volume of data that is now common place. However data is pointless without being able to process it in near real time. That's where Spark combined with Cassandra comes in! What was one just your storage system (Cassandra) can be transformed into an analytics system and it's really surprising how easy it is!
An overview of how MongoDB and Apache Spark are enabling IoT innovators to create new business models.
Presented at the Business of IoT meetup in London on Jan 13th 2016
Webinar: Rearchitecting Storage for the Next Wave of Splunk Data GrowthStorage Switzerland
Join Storage Switzerland and SwiftStack, a Splunk technology partner, for our webinar where our panel of experts will discuss the value of having Splunk analyze larger datasets while providing insight into overcoming infrastructure cost and complexity challenges through Splunk enhancements like SmartStore.
IoT Suite is an enterprise grade solution that allows you to get started quickly through a set of extensible pre-configured solutions for common IoT scenarios
How a Media Data Platform Drives Real-time Insights & Analytics using Apache ...Databricks
Roularta is a leading publishing company in Belgium. As digital news and channels move at a rapid pace and contain massive volumes of data, Roularta decided in 2019 to invest in a Spark-based data platform to drive true real-time website analytics and unlock insights on previously untouched (big) data sources. In this talk we’ll first explain why and how Roularta embarked from a classical data warehouse to a Spark-based Lakehouse using Delta. We’ll outline the series of publishing & marketing use-cases done in the last 12 months and highlight for each use-case the advantages of Spark and how the team further tuned performance to truly deliver insights with high velocity.
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager...Dataconomy Media
Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager at HPE, presented "Using advanced analytics functions of HPE Vertica for the following use cases: IoT, clickstream, machine data, integration with Hadoop & Kafka …" as part of the Big Data, Budapest v 3.0 meetup organised on the 19th of May 2016 at Skyscanner's headquarters.
Emerging Prevalence of Data Streaming in Analytics and it's Business Signific...Amazon Web Services
Learning Objectives:
- Get an overview of streaming data and it's application in analytics and big data.
- Understand the factors driving the accelerating transformation of batch processing to real-time.
- Learn how you should plan for incorporating data streaming in your analytics and processing workloads.
Business can now easily perform real-time analytics on data that has been traditionally analyzed using batch processing in data warehouses or using Hadoop frameworks, and react to new information in minutes or seconds instead of hours or days. In this webinar, Forrester analyst Mike Gualtieri and Amazon Kinesis GM Roger Barga will discuss this prevalent trend, it's business significance, and how you should plan for it. You will also learn about the AWS services that can help you get started quickly with real-time, streaming applications fore your analytics and big data workloads.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
A Winning Strategy for the Digital EconomyEric Kavanagh
The speed of innovation today creates tremendous opportunities for some, existential threats for others. Companies that win create their own success by leveraging modern data platforms. While architectures vary, the foundation is often in-memory, and the latency is real-time. Register for this Special Edition of The Briefing Room to hear veteran Analyst Dr. Robin Bloor explain how today's data platforms enable the modern enterprise in groundbreaking ways. He'll be briefed by Chris Hallenbeck of SAP who will demonstrate how forward-looking companies are leveraging real-time data platforms to achieve operational excellence, make decisions faster, and find new ways to innovate.
IBM's Watson is a machine-learning platform that’s been built to mirror the same learning process that humans have: Observe, Interpret, Evaluate and Decide. Through the use of this cognitive framework, Watson can search through a database of information and pull out key insights to bridge gaps in human knowledge. It’s expertise scaling for enterprise.
Watson has already helped businesses across a variety of industries increase their customer engagement, data discovery and informed decision making abilities. Is your business next?
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...Timothy Spann
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipelines
https://www.meetup.com/futureofdata-newyork/events/298660453/
Unlocking Financial Data with Real-Time Pipelines
(Flink Analytics on Stocks with SQL )
By Timothy Spann
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data. I will be utilizing NiFi 2.0 with Python and Vector Databases.
Timothy Spann
Principal Developer Advocate, Cloudera
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
https://twitter.com/PaaSDev
https://www.linkedin.com/in/timothyspann/
https://medium.com/@tspann
https://github.com/tspannhw/FLiPStackWeekly/
Using real time big data analytics for competitive advantageAmazon Web Services
Many organisations find it challenging to successfully perform real-time data analytics using their own on premise IT infrastructure. Building a system that can adapt and scale rapidly to handle dramatic increases in transaction loads can potentially be quite a costly and time consuming exercise.
Most of the time, infrastructure is under-utilised and it’s near impossible for organisations to forecast the amount of computing power they will need in the future to serve their customers and suppliers.
To overcome these challenges, organisations can instead utilise the cloud to support their real-time data analytics activities. Scalable, agile and secure, cloud-based infrastructure enables organisations to quickly spin up infrastructure to support their data analytics projects exactly when it is needed. Importantly, they can ‘switch off’ infrastructure when it is not.
BluePi Consulting and Amazon Web Services (AWS) are giving you the opportunity to discover how organisations are using real time data analytics to gain new insights from their information to improve the customer experience and drive competitive advantage.
Data APIs as a Foundation for Systems of EngagementVictor Olex
APIs have finally crossed over to the world of enterprise software, data analytics and application integration. Spearheaded by Amazon, propagated by internet startups and now adopted by the largest of businesses including Wall Street top firm Goldman Sachs - the APIs are here to stay. In this presentation we are linking all the facts and examine the opportunities stemming from Resource Oriented Architecture - a holistic approach to API implementation in large organizations.
Functionalities in AI Applications and Use Cases (OECD)AnandSRao1962
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.
Open Blueprint for Real-Time Analytics in Retail: Strata Hadoop World 2017 S...Grid Dynamics
This presentation outlines key business drivers for real-time analytics applications in retail and describes the emerging architectures based on In-Stream Processing (ISP) technologies. The slides present a complete open blueprint for an ISP platform - including a demo application for real-time Twitter Sentiment Analytics - designed with 100% open source components and deployable to any cloud.
To learn more, read an adjoining blog series on this topic here : https://blog.griddynamics.com/in-stream-processing-service-blueprint
Denodo DataFest 2017: Lowering IT Costs with Big Data and Cloud ModernizationDenodo
Watch the live presentation on-demand now: https://goo.gl/QanW35
Organizations are fast adapting cloud to lower the IT costs, and increase agility.
Watch this Denodo DataFest 2017 session to discover:
• How Logitech migrated their on-premise data warehouse and big data systems to the cloud and minimizing costs and immensely improved their time-to-market.
• The four main challenges Logitech faced when moving their data to the cloud.
• The benefits of adding a data virtualization layer to your data architecure.
IoT is reshaping the manufacturing and industrial processes, effectively changing the paradigm from one of repair and replace to more of predict and prevent. Using data streaming from connected equipment and machinery, organizations can now monitor the health of their assets and effectively predict when and how an asset might fail. However, without the right data management strategy and tools, investments in IoT can yield limited results. Join Cloudera and Tata Consultancy Services (TCS) for a joint webinar to learn more about how organizations are using advanced analytics and machine learning to drive IoT enabled predictive maintenance.
The strategic relationship between Hortonworks and SAP enables SAP to resell Hortonworks Data Platform (HDP) and provide enterprise support for their global customer base. This means SAP customers can incorporate enterprise Hadoop as a complement within a data architecture that includes SAP HANA and SAP BusinessObjects enabling a broad range of new analytic applications.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
1. www.accureanalytics.com
A big data analytics company
info@accureanalytics.com
Realtime Stream Analytics
with Momentum
Shamshad Ansari
President & CEO
4. www.accureanalytics.com4
RDBMS
News
channels
Click stream
Online chat
Network
Data
Sensor Data
Social
Media
Server Log
Call Log
Campaign
Data
TCP/IP
Subscription
3rd Party
Data
NoSQL
Others …
Data
Ingestion &
Transformati
on
Guzzler
Historical
Batch
Realtime
Hadoop Distributed File System (HDFS)
Neuron
MapReduce /
Stream
Processor
Machine
Learning
NLP
Math /
Statistics
Emitter
HDFS
NoSQL
Solr
Others…
Sink
NoSQL DB
Solr Cloud
Cassandra
HBase
HP Vertica
Others …
Analytics Visualizer
Tableau Qlik MicroStrategy Pentaho
Accure
Custom
5. www.accureanalytics.com
Stream Analytics with Momentum
• Process millions of events per second in
realtime
• Construct business specific alerts over data
from devices and applications
• Correlate data from multiple streams and
derive meaningful insights
• Apply machine learning on data streams in
realtime or in batch
5
6. www.accureanalytics.com
Stream Hub
• Momentum provides UI based configuration
utility, callled Stream Hub, to add any number
of devices or group of devices that will
transmit streams in realtime
• Streams of data from each device or group of
devices can be processed with different
algorithms
6
9. www.accureanalytics.com
Alert Mechanism
• Momentum provides an easy to use UI based
configuration utility to define rules to develop
alerts.
• Generated alerts can be consumed by other
third party applications/systems.
9
12. www.accureanalytics.com
Accure Engineers Momentum
Accure helps data driven companies to connect
to all data sources, aggregate, join and
transform their data, build big data analytics
based on machine learning, NLP, and statistical
science so that our customers get actionable
insights in a fraction of time and cost.
12