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Introduction To IPaaS: Drivers, Requirements And Use Cases
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Useful to: - Enterprise architects leading cloud and big data adoption strategies - Data engineers struggling with legacy ETL tools - Cloud application owners moving away from legacy ESB technologies - CTOs and CDOs driving change in enterprise IT In this interactive presentation, we’ll introduce you to iPaaS, how it’s different than legacy application and data integration and outline the 4 primary use cases in the modern enterprise. You’ll also get an introduction to SnapLogic, the industry’s first unified application and data integration platform built for self-service. Original copy at https://www.synerzip.com/webinar/introduction-to-ipaas-drivers-requirements-and-use-cases-july-20-2016/
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Introduction To IPaaS: Drivers, Requirements And Use Cases
- Introduction to iPaaS Drivers, Requirements and Use Cases Darren Cunningham, VP Marketing SnapLogic
- ©SnapLogic 2 Today’s Agenda • What is iPaaS and what are the drivers? • The new integration requirements • Introduction to SnapLogic • 4 primary iPaaS use cases • Why SnapLogic? • Next steps • Discussion
- ©SnapLogic 3 What is iPaaS? Integration Platform as a Service (iPaaS) is a suite of cloud services enabling development, execution and governance of integration flows connecting any combination of on premises and cloud-based processes, services, applications and data within individual or across multiple organizations.
- ©SnapLogic 4 CSV Big data and hybrid cloud environments are making yesterday’s approaches to integration obsolete
- ©SnapLogic 5 Data Is Eating the World “From now until 2020, the digital universe will about double every two years.” IDC, “The Digital Universe in 2020,” 2012.
- ©SnapLogic 6 Big Data Strains Traditional Techniques Top barriers to Big Data adoption: • Skills shortages • Integrating multiple data sources • Connecting big data technology with existing infrastructure
- ©SnapLogic 7 Hybrid is the New Normal, and Multicloud is Coming Databases On Prem Apps Big Data Firewall Cloud Apps and Data “…multicloud strategies will become common for 70 percent of organizations by 2019, up from less than 10 percent today.” – “What Data Center Architects Can Learn from Building Architects,” Gartner.com, October 2015. Hybrid SaaS and On Premises Environment
- ©SnapLogic 8 10 Requirements for Modern Integration 1. Application integration is done primarily through REST and SOAP services 2. Large-volume data integration is available to a Hadoop-based data lake or to cloud-based data warehouses 3. Integration has to support the continuum of data velocities starting from batch all the way to continuous streams 4. Integration is event-based rather than clock-driven 5. Integration is primarily document-centric 6. Integration is hybrid and spans cloud-cloud and cloud-ground scenarios 7. Integration itself has to be accessible through SOAP/REST APIs 8. Integration is all about connectivity, connectivity, connectivity 9. Integration has to be elastic 10. Integration has to be delivered as a service
- ©SnapLogic 9 The #1 Driver for iPaaS Adoption: SPEED
- ©SnapLogic 10 “The dilemma for enterprise IT organizations is that their legacy integration technologies were built before the era of big data, social, mobile and cloud computing and simply can’t keep up.” - Gaurav Dhillon, founder and CEO Our Investors
- ©SnapLogic 11 World Class Customers
- ©SnapLogic 12 Anything apps | data | APIs | things Anytime batch | streaming | real-time Anywhere on prem | cloud | hybrid
- ©SnapLogic 13 Connect Anything • Supports complex business processes point-to-point can’t handle • JSON-centric platform is more flexible and adaptable than XML/SOAP • 400+ pre-built Snaps
- ©SnapLogic 14 Connect Anytime Unified platform for self-service data and application integration DataVolume Latency ESB ETL • Low-latency, real-time, streaming • Batch and real-time Big Data integration
- ©SnapLogic 15 Connect Anywhere Cloud to Cloud Cloud to Ground Ground to Ground Hybrid SnapLogic separates execution from design to respect data gravity
- ©SnapLogic 16 4 Primary iPaaS Use Cases Hybrid Application Integration Cloud Data Warehouse/ Analytics Big Data Ingest- Transform- Deliver Retire Legacy Integration Platforms
- ©SnapLogic 17 Use Case: Hybrid Cloud Application Integration Multipoint integration between SaaS and on premises applications for business processes such as: • Quote-to-cash data flows • Employee onboarding/offboarding automation • Front-office / back-office integration • Trouble ticket resolution “We can do more in two hours with SnapLogic than we could in two days with traditional solutions.”
- ©SnapLogic 18 Salesforce Integration in a Snap Operational App Integration Analytical Data Integration
- ©SnapLogic 19 Use Case: Cloud Data Warehouse / Analytics Data ingestion and multipoint integration for virtually any data source for: • Data loading and aggregation • SQL and noSQL queries against data in the cloud • Empowering BI teams with self-service integration • Digital marketing effectiveness / customer 360 analytics “The datacenter became a limiting factor in a space where technology should be an enabler, so we moved to Amazon Web Services (AWS) platforms. Now, AWS is the platform and SnapLogic is the glue.”
- ©SnapLogic 20 SnapLogic for Connecting S3, Redshift, RDS, SQS and more with the rest of the enterprise
- ©SnapLogic 21 Use Case: Big Data and the Data Lake SnapLogic powers a modern data lake through: • Data ingestion: collect and integrate data from multiple sources • Data transformation: minimize the manual tasks associated with data shaping • Data delivery: make data processed on Hadoop or Spark easily available to off-cluster applications and data stores
- ©SnapLogic 22 z Data Acquisition Data Access z Data Management Add information and improve data Spark Python Scala Java R Pig Collect and integrate data from multiple sources HDFS AWS S3 MS Azure Blob On Prem Apps and Data • ERP • CRM • RDBMS Cloud Apps and Data • CRM • HCM • Social IoT Data • Sensors • Wearables • Devices Lakeshore Data Mart • MS Azure • AWS Redshift BI / Analytics • Tableau • MS PowerBI / Azure • AWS QuickSight Organize and prepare data for visualization HDFS AWS S3 MS Azure Blob Hive Batch Streaming Schedule and manage: Oozie, Ambari Kafka, Sqoop, Flume Real-time Impala, HiveSQL, SparkSQL Typical Data Lake Components
- ©SnapLogic 23 z Data Acquisition Data Access z Data Management The Modern Data Lake Powered by SnapLogic On Prem Apps and Data • ERP • CRM • RDBMS Cloud Apps and Data • CRM • HCM • Social IoT Data • Sensors • Wearables • Devices Lakeshore Data Mart • MS Azure • AWS Redshift BI / Analytics • Tableau • MS PowerBI / Azure • AWS QuickSight Batch Streaming Schedule and manage: SnapLogic Real-time Sort, Aggregate, Join, Merge, Transform SnapLogic abstracts and operationalizes with SnapReduce or Spark pipelines Collect and integrate data from multiple sources SnapLogic pipelines with standard mode execution Organize and prepare data for visualization SnapLogic pipelines with standard mode execution Pipeline Pipeline Pipeline Pipeline Pipeline Enterprise Data Lake Powered by SnapLogic
- ©SnapLogic 24 “Hadoop for Humans” This That “SnapLogic is democratizing data integration with a unified platform that enables nearly everyone to construct their own big and small data integrations across the enterprise and in the cloud.”
- ©SnapLogic 25 Use Case: Replace Legacy Integration Platforms Reduce “technical debt” from legacy integration platforms not designed for the cloud or Big Data • Reduce spending on expensive support contracts • Reduce time spent building and maintaining integrations • Become less reliant on costly consultants and experts “We’ve been able to eliminate some of the rigidity and time- consuming tasks related to traditional integration patterns.” RESTful Driver: Digital Transformation
- ©SnapLogic 26 Self-Service: A Primary SnapLogic Advantage Enabling: • Citizen Integrators • Ad Hoc Integrators • Advanced Integrators “Most CIOs have yet to recognize that their traditional, established integration strategies cannot cope with digitalization's fast technology innovation and accelerated pace of business.”
- ©SnapLogic 27 Why Do Customers Choose SnapLogic?
- ©SnapLogic 28 Unified Platform for Data and Application Integration “Unnecessarily segregated application and data integration efforts lead to counterproductive practices and escalating deployment cost.”
- ©SnapLogic 29 Self-Service User Interface • Cloud-based designer, dashboard • Drag & drop HTML5 interface • Reusable patterns and sub-pipelines “In one SnapLogic training session we were able to build 5 processes that were operational in 4 hours. It’s a night and day difference in the level of effort. We were blown away by the simplicity of the SnapLogic solution.”
- ©SnapLogic 30 Modern Architecture With Elastic Scale-Out • Each Snaplex can elastically expand and contract based on data traffic • Automatically handle variable traffic loads Firewall
- ©SnapLogic 31 Connected Library of 400+ Snaps Pre-built Connectors for: • SaaS applications • On premises applications • Big Data platforms • Databases • BI/analytics tools • Social media • Sort, Join, Parse and other transformations • REST, SOAP, JSON, more • SDK for custom development
- ©SnapLogic 32 Why Do Customers Choose SnapLogic? Unified platform for data and apps • Batch, streaming, real-time • High volume, variety, and velocity big data Self-service, intuitive UX • Intuitive for self- service users • Powerful and fast for experts Modern, elastic architecture • Scale-out elastic architecture • In the cloud, on prem, on Hadoop or Spark cluster Connected library of Snaps • Applications, analytics, big data, social media • REST, SOAP, JSON, transform Snaps, 300+ more
- ©SnapLogic 33 Next Steps: • Learn more about iPaaS – download the Magic Quadrant: www.snaplogic.com/Gartner-MQ • Identify a use case and get started. 3 areas to focus on: • Digital transformation initiative (new leadership, products, M&A) • Cloud adoption • New analytics
- ©SnapLogic 34 Integrate at the speed of modern business +1 888-494-1570 sales@snaplogic.com @SnapLogic www.snaplogic.com Discussion
- ©SnapLogic 35 Punkaj Jain punkaj@synerzip.com +1.510.509.8447
- ©SnapLogic 36 Synerzip Accelerate the delivery of your product roadmap Address technology skill gaps Save at least 50% with offshore software development Augment your team with optional on-site professionals Your trusted outsourcing partner for Agile software product development.
- ©SnapLogic 37 Synerzip Clients
- ©SnapLogic 38 Next Webinar AGILE2016 Conference Top 10 on Tuesday, August 16, 2016 at 10am CST Webinar Presenter: Hemant Elhence, CEO, Synerzip And Vinayak Joglekar, CTO, Synerzip
- ©SnapLogic 39 Connect with Synerzip @Synerzip linkedin.com/company/synerzip facebook.com/Synerzip Punkaj Jain punkaj@synerzip.com +1.510.509.8447
Hinweis der Redaktion
- Connecting applications or data from multiple sources is not new – ESB, SOA, ETL have been around for a long time. But the old ways are not keeping up with today’s realities…
- We all know that “data is eating the world.” Not only data from new sources such as wearables and sensors, but the sheer volume. The digital universe is doubling every two years and should reach 40,000 exabytes, or 40 trillion gigabytes by 2020.
- Gartner conducts an annual survey of IT executives worldwide regarding their adoption of Big Data tools and techniques and many report challenges on their Big Data journey. Each year three items have been cited among the top 10 challenges or hurdles to Big Data adoption: Shortage of people with relevant skills Problems integrating multiple data sources Connecting Big Data technology with existing infrastructure All of these challenges can be overcome with SnapLogic.
- Most organizations today have “hybrid” environments with systems on premises and in the cloud – if integration isn’t seamless, these can become information silos. Becoming more common: multicloud, where organizations are managing a combination of private and public clouds from different vendors. This presents integration challenges that legacy systems simply cannot support.
- These new requirements have given rise to a new category of integration called integration platform as a service (iPaaS), which should be built from the ground up to address the new and legacy enterprise application and data integration needs.
- Our founder, Gaurav Dhillon, saw this change coming. He founded Informatica and led it to a successful IPO, so he knew that these legacy technologies weren’t going to keep up. He founded SnapLogic specifically to address the new era of data. Andreessen Horowitz and Ignition believed in his vision and are our lead investors. And we have a growing roster of enterprises across a number of industries who have chosen SnapLogic as their platform of choice for data and application integration.
- Leading enterprises choose SnapLogic because we help them connect data and applications faster. We connect anything: sources including applications, APIs, things, or data We connect anytime: in batches, streaming, or in real time And we connect anywhere: on premises, in the cloud or a combination of both
- SnapLogic’s modern, elastic architecture supports hybrid environments. We like to say that SnapLogic “respects data gravity” and runs as close to the data as need be. If you are integrating only cloud applications, it would make no sense to run your integrations behind the firewall. Similarly, if you’re doing ground to ground or cloud to ground, you may want to run your Snaplex on premises or on a private cloud. With SnapLogic, you can run all of these integrations with a single platform.
- This is just a sampling of the available technologies that may go into a data lake. To date, most data lake deployments have been built through manual coding, open source tools and custom integration. Manual coding of data processing applications is common because data processing is thought of in terms of application-specific work. Unfortunately, this manual effort is a dead-end investment over the long term because the underlying technologies are constantly changing. Older data warehouse environments and ETL type integration tools are good at what they do, but they can’t meet many of the new needs. The new environments are focused on data processing, but require a lot of manual work. The data lake must incorporate aspects of old data warehouse environments like connecting to and extracting data from ERP or transaction processing systems, yet do this without clunky and inefficient tools like Sqoop. The data lake also must support new capabilities like reliable collection of large volumes of events at high speed and timely processing to make data available immediately. It must also support data coming from multiple sources in a hybrid model. This exceeds the abilities of traditional data integration tools.
- SnapLogic accelerates development of a modern data lake through: Data acquisition: collecting and integrating data from multiple sources. SnapLogic goes beyond developer tools such as Sqoop and Flume with a cloud-based visual pipeline designer, and pre-built connectors for 300+ structured and unstructured data sources, enterprise applications and APIs. Data transformation: adding information and transforming data. SnapLogic minimizes the manual tasks associated with data shaping and makes data scientists and analysts more efficient. SnapLogic includes Snaps for tasks such as transformations, joins and unions without scripting. Data access: organizing and preparing data for delivery and visualization. SnapLogic makes data processed on Hadoop or Spark easily available to off-cluster applications and data stores such as statistical packages and business intelligence tools.
- SnapLogic for big data integration benefits include: Improved Big Data Acquisition: Instantaneous access to hundreds of data sources from within Hadoop via pre-built connectors, called Snaps. Going beyond developer tools like Sqoop and Flume, SnapLogic allows Hadoop users to access and introspect cloud and on-premises data sources in an easy-to-use graphical interface. Double Data Scientist Productivity: Most data scientists spend the majority of their time on cumbersome coding tasks, data gathering and data preparation. SnapReduce 2.0 doubles data scientist productivity by simplifying complex data shaping tasks such as transformations, joins and unions. We call it Hadoop for Humans. Universal Big Data Delivery: Make Hadoop data and analytics results easily available to off-cluster applications and data stores such as statistical packages and business intelligence (BI) or visualization tools.
- Unified: At SnapLogic, we’re 100% focused on delivering a single, unified platform that can handle ETL (or ELT) requirements and low-latency ESB requirements. Productive: When we talk about connecting faster, a bit part of that is the productivity gains that our customers tell us about. Integration is a hard problem to solve, and we’re focused on simplifying it as much as possible with a very easy to use, drag and drop design interface for both citizen and advanced integrators. Modern: the SnapLogic modern architecture goes back to our ability to handle both real-time, low-latency integration requirements as well as big data volume, variety and velocity. And finally, Connected. You’ll see in the demonstration the breadth and depth of our Snaps. We have over 300 Snaps and a Snap Development Kit (SDK) for building custom Snaps.
- According to a recent Gartner report: “Unnecessarily segregated application and data integration efforts lead to counterproductive practices and escalating deployment cost.”
- When we talk about connecting faster, a bit part of that is the productivity gains that our customers tell us about. Integration is a hard problem to solve, and we’re focused on simplifying it as much as possible with a very easy to use, drag and drop design interface for both self-service and advanced integrators. As you can see from Adobe, who has over 100 users of SnapLogic today, they’re able to do more in 2 hours with our cloud integration service than they could do in 2 days with traditional solutions.
- Each Snaplex – whether a cloudplex, groundplex, or Hadooplex – can elastically expand and contract based on data traffic. The unit of scalability inside Snaplex is a JVM. Each Snaplex is initialized with a preconfigured number of JVMs (say one, for example). Once the utilization of that one JVM reaches a certain threshold (say 80%), a new JVM is automatically spun up to handle any additional workload. Once this excess data traffic has been processed and the second JVM is sitting idle, it gets torn down to scale back in to its original size.
- And finally, Connected. You’ll see in the demonstration the breadth and depth of our Snaps. We have over 300 Snaps and a Snap Development Kit (SDK) for building custom Snaps. Reference: http://www.snaplogic.com/snaps
- Why do customers choose SnapLogic over the alternatives? Unified: At SnapLogic, we’re 100% focused on delivering a single, unified platform that can handle ETL (or ELT) requirements and low-latency ESB requirements. Self-service: When we talk about connecting faster, a bit part of that is the productivity gains that our customers tell us about. Integration is a hard problem to solve, and we’re focused on simplifying it as much as possible with a very easy to use, drag and drop design interface for both citizen and advanced integrators. Modern: the SnapLogic modern architecture goes back to our ability to handle both real-time, low-latency integration requirements as well as big data volume, variety and velocity. And finally, Connected. You’ll see in the demonstration the breadth and depth of our Snaps. We have over 300 Snaps and a Snap Development Kit (SDK) for building custom Snaps.
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