Organizations storing large volumes of data in Amazon Redshift rely on faster cycle analysis to quickly uncover actionable insights. Their challenge when data volumes grow in Redshift is finding an analysis solution that removes the headaches of tedious ETL, data wrangling and allows scalable, visual data analysis. These slides shared during the webinar demonstrates ClearStory Data’s solution for scalable, fast-cycle, visual data analysis, that is used by CPG, Retail, Consumer Internet companies on Redshift.
To watch the on-demand webinar, visit:
In this presentation, Stephanie McReynolds from ClearStory Data describes the company's Data Intelligence Platform.
"Data access and analysis were once relegated to specialists, quants or statisticians. Today, competitiveness on the front lines of business is dictated by the speed of data access and the quality of informed decision-making. ClearStory is an integrated Application & Platform speeding analysis across internal & external data."
Learn more: http://www.clearstorydata.com
Watch the video presentation: http://wp.me/p3RLEV-1uI
Top five trends that will dominate the Global 2000 data discussion in 2015.
Read the original blog titled, "2015: Removing Blind Spots and Bringing Data Intelligence to Everyone" at http://bit.ly/1xMBLWy
Big data, your data, all data - Frederik VandeputteInspireX
Big Data, Your Data, All Data, …fast insights through Microsoft BI.
If you take a look at latest Gartner Hype Cycle for Emerging Technologies, you will find Big Data at the peak of inflated expectations. What exactly is Big Data? How can you look at data in a completely different way? How do you exploit the economic value of Big Data, Your Data, All Data … with familiar Microsoft BI tools?
Rethink Analytics with an Enterprise Data HubCloudera, Inc.
Have you run into one or more of the following barriers or limitations with your existing data warehousing architecture:
> Increasingly high data storage and/or processing costs?
> Silos of data sources?
> Complexity of management and security?
> Lack of analytics agility?
In this presentation, Stephanie McReynolds from ClearStory Data describes the company's Data Intelligence Platform.
"Data access and analysis were once relegated to specialists, quants or statisticians. Today, competitiveness on the front lines of business is dictated by the speed of data access and the quality of informed decision-making. ClearStory is an integrated Application & Platform speeding analysis across internal & external data."
Learn more: http://www.clearstorydata.com
Watch the video presentation: http://wp.me/p3RLEV-1uI
Top five trends that will dominate the Global 2000 data discussion in 2015.
Read the original blog titled, "2015: Removing Blind Spots and Bringing Data Intelligence to Everyone" at http://bit.ly/1xMBLWy
Big data, your data, all data - Frederik VandeputteInspireX
Big Data, Your Data, All Data, …fast insights through Microsoft BI.
If you take a look at latest Gartner Hype Cycle for Emerging Technologies, you will find Big Data at the peak of inflated expectations. What exactly is Big Data? How can you look at data in a completely different way? How do you exploit the economic value of Big Data, Your Data, All Data … with familiar Microsoft BI tools?
Rethink Analytics with an Enterprise Data HubCloudera, Inc.
Have you run into one or more of the following barriers or limitations with your existing data warehousing architecture:
> Increasingly high data storage and/or processing costs?
> Silos of data sources?
> Complexity of management and security?
> Lack of analytics agility?
What is the value of big data? How does a user get that value?
Before, analysts would have to wait months relying on IT for a new report or make changes to an existing one. Now, analysts are able to shrink that time down to days or even minutes. On top of that, analysts can ask questions that were not possible before. In this webinar, we’ll show you how this analysis is possible and the value that has been achieved by customers.
In this session, you will learn:
How analysts get value out of big data
How to visualize data at every step of analysis
How analysts can do big data analytics without IT, in one product
Strategy session 5 - unlocking the data dividend - andy steerAndy Steer
"A recent study completed by IDC examined the economic benefits accrued to organisations that made basic levels of investment in distinct areas of analytics and data management compared with the benefits accrued by organisations that opted for a broader and more diverse set of investments. The conclusion was that the leading organisations expect to capture in excess of $1.5 trillion more in value from their data and analytics initiatives over the next 4 years. This represents a 60% higher data dividend for the leading organisations.
To achieve these benefits organisations need to embrace the changing reality of the new data driven society and make a break from the beliefs and best practices inherent in traditional Business Intelligence programmes.
During the presentation Andy will expand on the data dividend concept, outline the 4 key investment areas that should be getting your attention and perhaps most importantly, explain how your existing SAP BusinessObjects technology can help you take your share of the estimated £53 billion UK data dividend."
Moving from data to insights: How to effectively drive business decisions & g...Cloudera, Inc.
Firms have become obsessed with data. But the key to competitive advantage is not just more or bigger data or big data technology, it is finding actionable insights from all the data as well as embedding insight in processes and applications. This requires a change in your approach - modernized architecture and embedding insights and data in you business decisions It also requires a change in how your people work systematically to find, test and implement insights. In this webinar, Forrester Vice President and Principal Analyst Brian Hopkins will present results from two years of research into these ideas and recommend to attendees how they can get the most out of their data and analytics to drive effective business decisions and gain competitive advantage.
Using Machine Learning to Understand and Predict Marketing ROIDATAVERSITY
Marketing is all about attracting, retaining and building profitable relationships with your customers, but how do you know which customers to target, which campaigns to run, and which marketing programs to invest in, to get most return for your dollar?
Join Alteryx and Keyrus as we demonstrate how to combine all relevant marketing, sales and customer data, and perform sophisticated analytics to deepen customer insight and calculate ROI of marketing programs.
You’ll walk away knowing how to:
Segment and profile your customers – take that raw data and translate it into real value
Build a marketing attribution model within Alteryx, creating a personal answer engine for your company.
Leverage R or Python code in an Alteryx workflow so data scientists can collaborate with non-coding stake holders in a code-friendly and code-free environment.
Join Alteryx and Keyrus and get the actionable insights you need to drive marketing ROI analytics, and answer million-dollar questions without spending millions of dollars on standardized solutions.
The promise of self-service analytics asserts that business users should be empowered make data-driven decisions quickly without having to involve the analytics team, while critics say that it could lead to faulty choices. In this presentation we’ll cover topics such as acknowledging diverse customer needs, choosing the right tools, understanding the pitfalls, and considering the future of self-service analytics. And cake.
IBM Governed data lake is a value-driven big data platform journey. The journey starts by ingesting wide variety of data, governing it, applying data science and machine learning on it to produce actionable insights.
Big Data Analytic with Hadoop: Customer StoriesYellowfin
Why watch?
Looking to analyze your growing data assets to unlock real business benefits today? But, are you sick of all the Big Data hype and whoopla?
Watch this on-demand Webinar from Actian and Yellowfin – Big Data Analytics with Hadoop – to discover how we’re making Big Data Analytics fast and easy:
Learn how a telecommunications provider has already transformed its business using Big Data Analytics with Hadoop.
Hold on as we go from data in Hadoop to predictive analytics in just 40-minutes.
Learn how to combine Hadoop with the most advanced Big Data technologies, and world’s easiest BI solution, to quickly generate real business value from Big Data Analytics.
What will you learn?
Discover how Actian’s market-leading Big Data Analytics technologies, combined with Yellowfin’s consumer-oriented platform for reporting and analytics, makes generating value from Big Data Analytics faster and easier than you thought possible.
Join us as we demonstrate how to:
• Connect to, prepare and optimize Big Data in Hadoop for reporting and analytics.
• Perform predictive analytics on streaming Big Data: Learn how to empower all your analytics stakeholders to move from historical reports to predictive analytics and gain a sustainable competitive advantage.
• Communicate insights attained from Big Data: Optimize the value of your Big Data insights by learning how to effectively communicate analytical information to defined user groups and types.
This Webinar is ideal if…
• You want to act on more data and data types in shorter timeframes
• You want to understand the steps involved in achieving Big Data success – both front and back end
• You want to see how market leaders are leveraging Big Data to become data-driven organizations today
Looking to analyze and exploit Big Data assets stored in Hadoop? Then this Webinar is a must.
Using neo4j for enterprise metadata requirementsNeo4j
Metadata is everywhere yet traditionally approaches to managing it have been disparate, siloed and often ineffective.
In this talk James will discuss the opportunities for using graph technology to address the fundamental challenges and questions of metadata management such as impact analysis, data lineage and definitions.
Data to Value are a Data Consultancy based in London that specialise in applying lean and agile techniques to complex data requirements. Connected Data is a particular focus for the firm which they see as the new frontier for data leaders.
James Phare has over 15 years experience of creating and leading data teams in various roles in Financial Services. Prior to cofounding Data Consultancy Data to Value he was Head of Information Management and Data Architecture at Man Group – one of the world’s largest Hedge funds. James started his career at Thomson Reuters after graduating in Economics from the University of York.
8.17.11 big data and hadoop with informatica slideshareJulianna DeLua
This presentation provides a briefing on Big Data and Hadoop and how Informatica's Big Data Integration plays a role to empower the data-centric enterprise.
Graphically understand and interactively explore your Data LineageMohammad Ahmed
Graphically understand and interactively explore your Data Lineage:
Data Lineage for ER/Studio gives data management professionals and business users essential insight to the extracts, transformations, and loads of complex enterprise data. Data governance and organizational compliance is supported with detailed metadata management for risk reduction and data discrepancy isolation.
In this presentation we look at the key reasons for using ER/Studio Data Lineage and what it provides you with.To learn more about ER/Studio Data Lineage please look here: http://www.embarcadero.com/products/er-studio-data-lineage or request a demo here: http://forms.embarcadero.com/forms/ERStudioProductInterest
This is my presentation from the recent Mastering BI event in Melbourne. Consumers of information expect experiences and visualizations similar to their personal solutions, we need to start thinking in terms of Analytic Applications - purpose built solutions that enable people to ask a question, get an answer and move on.
What is the value of big data? How does a user get that value?
Before, analysts would have to wait months relying on IT for a new report or make changes to an existing one. Now, analysts are able to shrink that time down to days or even minutes. On top of that, analysts can ask questions that were not possible before. In this webinar, we’ll show you how this analysis is possible and the value that has been achieved by customers.
In this session, you will learn:
How analysts get value out of big data
How to visualize data at every step of analysis
How analysts can do big data analytics without IT, in one product
Strategy session 5 - unlocking the data dividend - andy steerAndy Steer
"A recent study completed by IDC examined the economic benefits accrued to organisations that made basic levels of investment in distinct areas of analytics and data management compared with the benefits accrued by organisations that opted for a broader and more diverse set of investments. The conclusion was that the leading organisations expect to capture in excess of $1.5 trillion more in value from their data and analytics initiatives over the next 4 years. This represents a 60% higher data dividend for the leading organisations.
To achieve these benefits organisations need to embrace the changing reality of the new data driven society and make a break from the beliefs and best practices inherent in traditional Business Intelligence programmes.
During the presentation Andy will expand on the data dividend concept, outline the 4 key investment areas that should be getting your attention and perhaps most importantly, explain how your existing SAP BusinessObjects technology can help you take your share of the estimated £53 billion UK data dividend."
Moving from data to insights: How to effectively drive business decisions & g...Cloudera, Inc.
Firms have become obsessed with data. But the key to competitive advantage is not just more or bigger data or big data technology, it is finding actionable insights from all the data as well as embedding insight in processes and applications. This requires a change in your approach - modernized architecture and embedding insights and data in you business decisions It also requires a change in how your people work systematically to find, test and implement insights. In this webinar, Forrester Vice President and Principal Analyst Brian Hopkins will present results from two years of research into these ideas and recommend to attendees how they can get the most out of their data and analytics to drive effective business decisions and gain competitive advantage.
Using Machine Learning to Understand and Predict Marketing ROIDATAVERSITY
Marketing is all about attracting, retaining and building profitable relationships with your customers, but how do you know which customers to target, which campaigns to run, and which marketing programs to invest in, to get most return for your dollar?
Join Alteryx and Keyrus as we demonstrate how to combine all relevant marketing, sales and customer data, and perform sophisticated analytics to deepen customer insight and calculate ROI of marketing programs.
You’ll walk away knowing how to:
Segment and profile your customers – take that raw data and translate it into real value
Build a marketing attribution model within Alteryx, creating a personal answer engine for your company.
Leverage R or Python code in an Alteryx workflow so data scientists can collaborate with non-coding stake holders in a code-friendly and code-free environment.
Join Alteryx and Keyrus and get the actionable insights you need to drive marketing ROI analytics, and answer million-dollar questions without spending millions of dollars on standardized solutions.
The promise of self-service analytics asserts that business users should be empowered make data-driven decisions quickly without having to involve the analytics team, while critics say that it could lead to faulty choices. In this presentation we’ll cover topics such as acknowledging diverse customer needs, choosing the right tools, understanding the pitfalls, and considering the future of self-service analytics. And cake.
IBM Governed data lake is a value-driven big data platform journey. The journey starts by ingesting wide variety of data, governing it, applying data science and machine learning on it to produce actionable insights.
Big Data Analytic with Hadoop: Customer StoriesYellowfin
Why watch?
Looking to analyze your growing data assets to unlock real business benefits today? But, are you sick of all the Big Data hype and whoopla?
Watch this on-demand Webinar from Actian and Yellowfin – Big Data Analytics with Hadoop – to discover how we’re making Big Data Analytics fast and easy:
Learn how a telecommunications provider has already transformed its business using Big Data Analytics with Hadoop.
Hold on as we go from data in Hadoop to predictive analytics in just 40-minutes.
Learn how to combine Hadoop with the most advanced Big Data technologies, and world’s easiest BI solution, to quickly generate real business value from Big Data Analytics.
What will you learn?
Discover how Actian’s market-leading Big Data Analytics technologies, combined with Yellowfin’s consumer-oriented platform for reporting and analytics, makes generating value from Big Data Analytics faster and easier than you thought possible.
Join us as we demonstrate how to:
• Connect to, prepare and optimize Big Data in Hadoop for reporting and analytics.
• Perform predictive analytics on streaming Big Data: Learn how to empower all your analytics stakeholders to move from historical reports to predictive analytics and gain a sustainable competitive advantage.
• Communicate insights attained from Big Data: Optimize the value of your Big Data insights by learning how to effectively communicate analytical information to defined user groups and types.
This Webinar is ideal if…
• You want to act on more data and data types in shorter timeframes
• You want to understand the steps involved in achieving Big Data success – both front and back end
• You want to see how market leaders are leveraging Big Data to become data-driven organizations today
Looking to analyze and exploit Big Data assets stored in Hadoop? Then this Webinar is a must.
Using neo4j for enterprise metadata requirementsNeo4j
Metadata is everywhere yet traditionally approaches to managing it have been disparate, siloed and often ineffective.
In this talk James will discuss the opportunities for using graph technology to address the fundamental challenges and questions of metadata management such as impact analysis, data lineage and definitions.
Data to Value are a Data Consultancy based in London that specialise in applying lean and agile techniques to complex data requirements. Connected Data is a particular focus for the firm which they see as the new frontier for data leaders.
James Phare has over 15 years experience of creating and leading data teams in various roles in Financial Services. Prior to cofounding Data Consultancy Data to Value he was Head of Information Management and Data Architecture at Man Group – one of the world’s largest Hedge funds. James started his career at Thomson Reuters after graduating in Economics from the University of York.
8.17.11 big data and hadoop with informatica slideshareJulianna DeLua
This presentation provides a briefing on Big Data and Hadoop and how Informatica's Big Data Integration plays a role to empower the data-centric enterprise.
Graphically understand and interactively explore your Data LineageMohammad Ahmed
Graphically understand and interactively explore your Data Lineage:
Data Lineage for ER/Studio gives data management professionals and business users essential insight to the extracts, transformations, and loads of complex enterprise data. Data governance and organizational compliance is supported with detailed metadata management for risk reduction and data discrepancy isolation.
In this presentation we look at the key reasons for using ER/Studio Data Lineage and what it provides you with.To learn more about ER/Studio Data Lineage please look here: http://www.embarcadero.com/products/er-studio-data-lineage or request a demo here: http://forms.embarcadero.com/forms/ERStudioProductInterest
This is my presentation from the recent Mastering BI event in Melbourne. Consumers of information expect experiences and visualizations similar to their personal solutions, we need to start thinking in terms of Analytic Applications - purpose built solutions that enable people to ask a question, get an answer and move on.
Predictive technology has always been in the realm on the Data Scientist - with our acquisition of KXEN we plan to change that - We are bring Predictive to the masses
SAP in APJ - The impact and importance of APJ on SAP & the WorldKurt J. Bilafer
This is a copy of a presentation I shared with ~80 Graduate students that visited Singapore from the University of Southern California. The conversation centered around the impact of Asia Pacific & Japan on SAP and the world as well as my personal experiences in the region.
This is a copy of my 2012 SAP Insider Singapore Keynote presentation. Here is the link to recording if you want to here the panel discussion as well http://www.youtube.com/watch?v=RYaz3r9fS2I
In Chip Biz Analytics - Innovation & Disruption
Amir Orad, CEO of Sisense
Video of this session at the Database Camp conference at the UN is on http://www.Database.Camp
This is the presentation I shared at the SAP Influencer Summit. The presentation discusses how we are seeing companies in APJ utilize our BI/Analytics solutions.
Keynote Presentation SAP Insider 2013 - SingaporeKurt J. Bilafer
This was a brief keynote presentation highlighting what business users (information consumers) are expecting from Analytics. I also have a few slides on how easy it is to share with SAP's broad ecosystem to help close the skills gap.
Building a real-time pipeline from scratch that is able to handle billion+ transactions per day, store, analyze and visualize it all in real-time has never been easier. In this build-as-we-go talk, we’ll create a front-to-back architecture that does exactly that.
* we’ll start with a simple producer emitting a few messages and publishing them onto a Kafka queue
* on consuming end of the queue a Spark-based Streamliner process will pick them up and store in MemSQL
* ZoomData will connect to MemSQL for real-time visualization where we’ll be able to ask various questions and see answers change as data is flowing through the system
* we’ll quickly make the entire pipeline more complex by increasing the amount of data as well as complexity of the data, until reaching 100K transactions per second
As we walk through this demo, we will touch on cross data-center Kafka and MemSQL set-ups, speed limitations if any as well as echo back to real-life use cases of a similar set-up used in Goldman’s Asset Management division for the purposes of Portfolio Management & Trading.
Antoine Genereux takes us on a detailed overview of the Database solutions available on the AWS Cloud, addressing the needs and requirements of customers at all levels. He also discusses Business Intelligence and Analytics solutions.
AWS Summit 2013 | India - Petabyte Scale Data Warehousing at Low Cost, Abhish...Amazon Web Services
Amazon Redshift is a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. In this session we'll give an introduction to the service and its pricing before diving into how it delivers fast query performance on data sets ranging from hundreds of gigabytes to a petabyte or more.
Learn best practices for building a real-time streaming data architecture on AWS with Spark Streaming, Amazon Kinesis, and Amazon Elastic MapReduce (EMR). Get a closer look at how to ingest streaming data scalably and durably from data producers like mobile devices, servers, and even web browsers, and design a stream processing application with minimal data duplication and exactly-once processing.
Presented by: Guy Ernest, Principal Business Development Manager, Amazon Web Services
Customer Guest: Harry Koch, Solutions Architecture, Philips
Data warehousing in the era of Big Data: Deep Dive into Amazon RedshiftAmazon Web Services
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.
Processing the volume and variety of data that today’s organizations produce can be both challenging and costly – especially with a legacy data warehouse. Combining the scale and performance of the cloud with AWS and APN Partner solutions for migration, integration, analysis, and visualization can help overcome these obstacles. With a modern data warehouse architecture, organizations can store, process, and analyze massive volumes of data of virtually any type. Register for this upcoming webinar, where Pearson - an education and media conglomerate - will share in detail how they built a scalable and flexible business intelligence platform on the cloud, with Tableau and AWS.
Learn how you can seamlessly load and transform data in Amazon Redshift with Matillion ETL and analyze it with Tableau. Hear how 47Lining and NorthBay can provide insights to guide you through migration with ease. Tableau will discuss best practices to analyze your data on AWS and share new insights throughout your organization.
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.
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the CloudAmazon Web Services
FINRA’s Data Lake unlocks the value in its data to accelerate analytics and machine learning at scale. FINRA's Technology group has changed its customer's relationship with data by creating a Managed Data Lake that enables discovery on Petabytes of capital markets data, while saving time and money over traditional analytics solutions. FINRA’s Managed Data Lake includes a centralized data catalog and separates storage from compute, allowing users to query from petabytes of data in seconds. Learn how FINRA uses Spot instances and services such as Amazon S3, Amazon EMR, Amazon Redshift, and AWS Lambda to provide the 'right tool for the right job' at each step in the data processing pipeline. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator.
This overview presentation discusses big data challenges and provides an overview of the AWS Big Data Platform by covering:
- How AWS customers leverage the platform to manage massive volumes of data from a variety of sources while containing costs.
- Reference architectures for popular use cases, including, connected devices (IoT), log streaming, real-time intelligence, and analytics.
- The AWS big data portfolio of services, including, Amazon S3, Kinesis, DynamoDB, Elastic MapReduce (EMR), and Redshift.
- The latest relational database engine, Amazon Aurora— a MySQL-compatible, highly-available relational database engine, which provides up to five times better performance than MySQL at one-tenth the cost of a commercial database.
Created by: Rahul Pathak,
Sr. Manager of Software Development
Webinar - Accelerating Hadoop Success with Rapid Data Integration for the Mod...Hortonworks
Many enterprises are turning to Apache Hadoop to enable Big Data Analytics and reduce the costs of traditional data warehousing. Yet, it is hard to succeed when 80% of the time is spent on moving data and only 20% on using it. It’s time to swap the 80/20! The Big Data experts at Attunity and Hortonworks have a solution for accelerating data movement into and out of Hadoop that enables faster time-to-value for Big Data projects and a more complete and trusted view of your business. Join us to learn how this solution can work for you.
Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce SPICE - a new Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
Presented by: Matthew McClean, AWS Partner Solutions Architect, Amazon Web Services
AWS Webcast - Sales Productivity Solutions with MicroStrategy and RedshiftAmazon Web Services
Sales Force Automation (SFA) and Customer Relationship Management (CRM) tools, such as Salesforce.com and Microsoft Dynamics CRM, are ubiquitous tools that provide all of the transactional capabilities required to manage a company's sales pipeline. SFA and CRM data alone, however, is limited and so combining it with information from other sources enables you to create unique and powerful insights. When combined with product and financial data, for example, get visibility into relationships between geographies, sales reps, product performance, and revenue to ultimately optimize profits. Layer on advanced analytic to make predictions about future product sales based on seasonality and other market conditions. To unleash the full power of the CRM and dramatically increase operational performance and top-line revenue, companies are leveraging advanced analytic and data visualization to deliver new insights to the entire sales organization. Moreover, delivering these sales enablement productivity solutions on mobile devices, ensures strong adoption across every sales team. Join us in this webinar to learn how to use MicroStrategy together with Amazon Redshift to build mobile sales productivity solutions for your business.
Amazon Web Services proporciona una amplia gama de servicios que le ayudarán a crear e implementar aplicaciones de análisis de big data de forma rápida y sencilla. AWS ofrece un acceso rápido a recursos de TI económicos y flexibles, algo que permitirá escalar prácticamente cualquier aplicación de big data con rapidez, incluidos almacenamiento de datos, análisis de clics, detección de elementos fraudulentos, motores de recomendación, proceso ETL impulsado por eventos, informática sin servidor y procesamiento del Internet de las cosas. Con AWS no necesita hacer grandes inversiones iniciales de tiempo o dinero para crear y mantener la infraestructura. En su lugar, puede aprovisionar exactamente el tipo y el tamaño adecuado de los recursos que necesita para impulsar sus aplicaciones de análisis de big data. Puede obtener acceso a tantos recursos como necesite, prácticamente al instante, y pagar únicamente por los utilice.
Customer value analysis of big data productsVikas Sardana
Business value analysis through Customer Value Model for software technology choices with a case study from Mobile Advertising industry for Big Data use case.
Modern Data Architectures for Business Insights at Scale Amazon Web Services
Using AWS to design and build your data architecture has never been easier to gain insights and uncover new opportunities to scale and grow your business. Join this workshop to learn how you can gain insights at scale with the right big data applications.
Building a real-time analytics solution has never been faster or more cost-efficient. Most organizations are trying to find a way to improve customer experience and respond to business events in real time. Importantly, to do this quickly and at a fraction of the price of traditional approaches. In this session we will look at how to use the AWS services to best meet your real-time analytics needs.
Similar to Fast Cycle, Multi-Terabyte Data Analysis with Amazon Redshift and ClearStory Data (20)
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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.
2. Today’s Speakers
2
Tina Adams
Senior Product Manager
Amazon Web Services
Andrew Yeung
Director, Product Marketing
ClearStory Data
Scott Anderson
Senior Sales Engineer
ClearStory Data
3. Agenda
• Overview of Amazon Redshift
• Fast Cycle Data Analysis with ClearStory Data on
Amazon Redshift
• Demo
• Q&A
3
5. Amazon Redshift Architecture
• Leader Node
– SQL endpoint
– Stores metadata
– Coordinates query execution
• Compute Nodes
– Local, columnar storage
– Execute queries in parallel
– Load, backup, restore via
Amazon S3; load from
Amazon DynamoDB or SSH
• Two hardware platforms
– Optimized for data processing
– DW1: HDD; scale from 2TB to 1.6PB
– DW2: SSD; scale from 160GB to 256TB
10 GigE
(HPC)
Ingestion
Backup
Restore
SQL Clients/BI Tools
128GB RAM
16TB disk
16 cores
Amazon S3 / DynamoDB / SSH
JDBC/ODBC
128GB RAM
16TB disk
16 cores
Compute
Node
128GB RAM
16TB disk
16 cores
Compute
Node
128GB RAM
16TB disk
16 cores
Compute
Node
Leader
Node
6. Amazon Redshift is priced to let you analyze all your data
• Number
of
nodes
x
cost
per
hour
• No
charge
for
leader
node
• No
upfront
costs
• Pay
as
you
go
DW1 (HDD)
Price Per Hour for
DW1.XL Single
Node
Effective Annual
Price per TB
On-Demand $ 0.850 $ 3,723
1 Year
Reservation
$ 0.500 $ 2,190
3 Year
Reservation
$ 0.228 $ 999
DW2 (SSD)
Price Per Hour for
DW2.L Single Node
Effective Annual
Price per TB
On-Demand $ 0.250 $ 13,688
1 Year
Reservation
$ 0.161 $ 8,794
3 Year
Reservation
$ 0.100 $ 5,498
7. Common Customer Use Cases
• Reduce costs by
extending DW rather than
adding HW
• Migrate completely from
existing DW systems
• Respond faster to
business
• Improve performance by
an order of magnitude
• Make more data
available for analysis
• Access business data via
standard reporting tools
• Add analytic functionality
to applications
• Scale DW capacity as
demand grows
• Reduce HW & SW costs
by an order of magnitude
Traditional Enterprise DW Companies with Big Data SaaS Companies
11. Consider the Following Question…
CPG/Retail
“Is daily product sales being impacted by
restocking rate, product freshness, store
merchandising, competitor pricing or
demographic buying patterns?”
Or…
12. Consider the Following Question…
Consumer Internet
“Who are my users, how long are they on the
system, what features are they accessing, how
do they decide what purchases to make?”
How would you find an answer, or uncover
new insight, on fast cycle?
13. Hurdles to Fast-Cycle Data Analysis
Proliferation of inconsistent, siloed views
Resulting Line-of-Business Pains
Lengthy round trip to
ask new questions
Resort to point solutions,
spreadsheets or desktop
visualization tools
Increased blind spots & slow decisions
No traceability to validate insights
Data Refresh
Velocity
Restrictions
Limited Data
Scale &
Data Formats
Slow Decision
Times
Skills Gap
Rigid Dashboards
Sampling of data
Limitations of Traditional Solutions
14. Date & Time
Location
Text
Currency
Categories
Numbers
ClearStory Data Solution Overview
More LOB Users
• Interactive StoryBoards
for fast answers for LOB
More Speed
• Reduce data
manipulation
• Automates data
blending
• Fast exploration
More Sources
• More internal sources/
formats
• Direct access to external
data
User&DataGovernance
Data Access Analysis/Exploration StoryBoards
Application
Data Steward Story Authors Business Users
Collaboration
Harmonization
Data Inference & Metadata
Platform
Date & Time
Location
Text
Currency
Categories
Numbers
Product Name
Product SKU
Product Cat
Product Brand
Zip Code
County
State
Internal Data External Data
Semi-
Structured
Structured Files API / Web Premium Public
Amazon
Redshift
15. Why ClearStory for Amazon Redshift?
Scale out as
data
volume
grows – no
constraints
Scalability
Less pre-
processing
and data
aggregation
Aggregation
Data
governance,
user
governance,
lineage and
traceability
Governance
Speed of
analysis –
enabled by
ClearStory’s
underlying
Spark-
based in-
memory
data
processing
Speed
Ease-of-use
on front-end
for any user.
Less
reliance on
users with
specialized
skillsets
Simplicity
16. Consumer Internet, Online Gaming
Need: Intra-Day Analysis on Large Volume Data Sets
16
Data
Captured
Gaming Platform
Amazon Redshift
Centralized
Data Store
Intra-Day,
Multi-
Terabyte
Analysis
with
ClearStory
Data
Understand user behavior based on usage patterns on online game.
Analyze drivers of in-app purchase revenue by partner source and user profile.
Partner NetworkBusiness Analyst
Executives
Collaboration
Event-based
Game Data
User Profile
Awards &
Promotions
In-App
Purchases
17. Leader in Dairy Products
How Are We Performing Daily by Grocery Store and Why?
17
Data
Sources
Internal Supply Chain Retailer’s Systems
Daily,
Fast-Cycle
Analysis
10+ Data Sources Blended Daily
Retailers / GrocersBusiness Analyst
Executives
Collaboration
Inventory Demand
Planning
Logistics VMI
Point-of-
Sales
Warehouse
Store
Shelves
Fill Rate
Syndicated Retail Sales Data
• Holistic customer
analysis
• Impacts of promos,
placement, price,
packaging
• Collaborative
insight for key
stakeholders and
grocers
Converge
Disparate Data
Data Platform
• Converge data silos
across the entire
supply chain
• Spot sales
opportunities and
competitive threats
• Speed of execution
driven by business
need
19. Summary
1. More Data
- More Internal/External sources and diverse data formats
- Plus direct access to Amazon Redshift
2. More Speed
- Eliminate data manipulation
- And automates data blending for fast answers
3. More Business Consumption of Data
- New simple user model for any skillset
- Interactive StoryBoards for fast answers for line-of-business