�ݺ�ߣshows by User: SumitSarkar10

�ݺ�ߣshows by User: SumitSarkar10 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: SumitSarkar10 / Thu, 15 Nov 2018 03:01:47 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: SumitSarkar10 What serverless means for enterprise apps /slideshow/what-serverless-means-for-enterprise-apps/123048455 whatserverlessmeansforenterpriseapps-campit-181115030147
There’s a new approach to app development ripe with misconceptions and more buzzwords to translate to business sponsors. Industry analysts call it serverless, but it’s also known as backend as a service (BaaS), function as a service (FaaS), cloud-native architectures, or microservices—just to name a few. Whatever you call it, this approach is giving developers new freedom to focus on frontend functionality and deliver better, more innovative user experiences and ultimately establish value faster. Let’s discuss the pros and cons of serverless in enterprise architectures.]]>
There’s a new approach to app development ripe with misconceptions and more buzzwords to translate to business sponsors. Industry analysts call it serverless, but it’s also known as backend as a service (BaaS), function as a service (FaaS), cloud-native architectures, or microservices—just to name a few. Whatever you call it, this approach is giving developers new freedom to focus on frontend functionality and deliver better, more innovative user experiences and ultimately establish value faster. Let’s discuss the pros and cons of serverless in enterprise architectures.]]> Thu, 15 Nov 2018 03:01:47 GMT /slideshow/what-serverless-means-for-enterprise-apps/123048455 SumitSarkar10@slideshare.net(SumitSarkar10) What serverless means for enterprise apps SumitSarkar10 There’s a new approach to app development ripe with misconceptions and more buzzwords to translate to business sponsors. Industry analysts call it serverless, but it’s also known as backend as a service (BaaS), function as a service (FaaS), cloud-native architectures, or microservices—just to name a few. Whatever you call it, this approach is giving developers new freedom to focus on frontend functionality and deliver better, more innovative user experiences and ultimately establish value faster. Let’s discuss the pros and cons of serverless in enterprise architectures. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatserverlessmeansforenterpriseapps-campit-181115030147-thumbnail.jpg?width=120&height=120&fit=bounds" /> There’s a new approach to app development ripe with misconceptions and more buzzwords to translate to business sponsors. Industry analysts call it serverless, but it’s also known as backend as a service (BaaS), function as a service (FaaS), cloud-native architectures, or microservices—just to name a few. Whatever you call it, this approach is giving developers new freedom to focus on frontend functionality and deliver better, more innovative user experiences and ultimately establish value faster. Let’s discuss the pros and cons of serverless in enterprise architectures.

What serverless means for enterprise apps from Sumit Sarkar

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0 Digitize Enterprise Assets for Mobility /slideshow/digitize-enterprise-assets-for-mobility/97528883 idevnews-webinar-mobility-final-180518183121
Demand for digital experiences such as mobility are putting pressure on enterprise teams and systems. Many of these systems are deployed on servers and not engineered to scale. Mobility projects across web/mobile, voice, chat and AR are increasingly running on serverless cloud native architectures. But how can organizations meet the customer demands for digital experiences on enterprise systems such as ERP systems or enterprise APIs? Join Progress Kinvey to explore four options to digitize enterprise systems to deliver experiences for the connected world.]]>
Demand for digital experiences such as mobility are putting pressure on enterprise teams and systems. Many of these systems are deployed on servers and not engineered to scale. Mobility projects across web/mobile, voice, chat and AR are increasingly running on serverless cloud native architectures. But how can organizations meet the customer demands for digital experiences on enterprise systems such as ERP systems or enterprise APIs? Join Progress Kinvey to explore four options to digitize enterprise systems to deliver experiences for the connected world.]]> Fri, 18 May 2018 18:31:21 GMT /slideshow/digitize-enterprise-assets-for-mobility/97528883 SumitSarkar10@slideshare.net(SumitSarkar10) Digitize Enterprise Assets for Mobility SumitSarkar10 Demand for digital experiences such as mobility are putting pressure on enterprise teams and systems. Many of these systems are deployed on servers and not engineered to scale. Mobility projects across web/mobile, voice, chat and AR are increasingly running on serverless cloud native architectures. But how can organizations meet the customer demands for digital experiences on enterprise systems such as ERP systems or enterprise APIs? Join Progress Kinvey to explore four options to digitize enterprise systems to deliver experiences for the connected world. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/idevnews-webinar-mobility-final-180518183121-thumbnail.jpg?width=120&height=120&fit=bounds" /> Demand for digital experiences such as mobility are putting pressure on enterprise teams and systems. Many of these systems are deployed on servers and not engineered to scale. Mobility projects across web/mobile, voice, chat and AR are increasingly running on serverless cloud native architectures. But how can organizations meet the customer demands for digital experiences on enterprise systems such as ERP systems or enterprise APIs? Join Progress Kinvey to explore four options to digitize enterprise systems to deliver experiences for the connected world.

Digitize Enterprise Assets for Mobility from Sumit Sarkar

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0 Data APIs Don't Discriminate [API World Stage Talk] /slideshow/data-apis-dont-discriminate-api-world-stage-talk/80221580 apiworldstage2017-170927153840
The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is driving a market demand to expose more data from APIs. Business analysts, data engineers, and data scientists have been getting left behind in existing API strategies. This is because many APIs are designed to integrate with applications to extend functionality, however these data workers are looking for APIs that facilitate direct data access to support analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers in this $30 billion market.]]>
The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is driving a market demand to expose more data from APIs. Business analysts, data engineers, and data scientists have been getting left behind in existing API strategies. This is because many APIs are designed to integrate with applications to extend functionality, however these data workers are looking for APIs that facilitate direct data access to support analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers in this $30 billion market.]]> Wed, 27 Sep 2017 15:38:40 GMT /slideshow/data-apis-dont-discriminate-api-world-stage-talk/80221580 SumitSarkar10@slideshare.net(SumitSarkar10) Data APIs Don't Discriminate [API World Stage Talk] SumitSarkar10 The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is driving a market demand to expose more data from APIs. Business analysts, data engineers, and data scientists have been getting left behind in existing API strategies. This is because many APIs are designed to integrate with applications to extend functionality, however these data workers are looking for APIs that facilitate direct data access to support analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers in this $30 billion market. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/apiworldstage2017-170927153840-thumbnail.jpg?width=120&height=120&fit=bounds" /> The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is driving a market demand to expose more data from APIs. Business analysts, data engineers, and data scientists have been getting left behind in existing API strategies. This is because many APIs are designed to integrate with applications to extend functionality, however these data workers are looking for APIs that facilitate direct data access to support analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers in this $30 billion market.

Data APIs Don't Discriminate [API World Stage Talk] from Sumit Sarkar

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0 SQL vs SOQL for Salesforce Analytics /slideshow/sql-vs-soql-for-salesforce-analytics/79946456 201606webinarsqlvssoqlforsalesforceanalytics-170919172840
Salesforce analytics and BI continues to be a trending, hot topic as organizations implement new platforms to improve their customer intelligence. But what’s the best way to access the data? SOQL is the popular query language for Salesforce. However, SQL may be better suited for accessing data for analytics. Join us in the great SOQL vs. SQL query debate to see which one is best for your analytics project.]]>
Salesforce analytics and BI continues to be a trending, hot topic as organizations implement new platforms to improve their customer intelligence. But what’s the best way to access the data? SOQL is the popular query language for Salesforce. However, SQL may be better suited for accessing data for analytics. Join us in the great SOQL vs. SQL query debate to see which one is best for your analytics project.]]> Tue, 19 Sep 2017 17:28:40 GMT /slideshow/sql-vs-soql-for-salesforce-analytics/79946456 SumitSarkar10@slideshare.net(SumitSarkar10) SQL vs SOQL for Salesforce Analytics SumitSarkar10 Salesforce analytics and BI continues to be a trending, hot topic as organizations implement new platforms to improve their customer intelligence. But what’s the best way to access the data? SOQL is the popular query language for Salesforce. However, SQL may be better suited for accessing data for analytics. Join us in the great SOQL vs. SQL query debate to see which one is best for your analytics project. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/201606webinarsqlvssoqlforsalesforceanalytics-170919172840-thumbnail.jpg?width=120&height=120&fit=bounds" /> Salesforce analytics and BI continues to be a trending, hot topic as organizations implement new platforms to improve their customer intelligence. But what’s the best way to access the data? SOQL is the popular query language for Salesforce. However, SQL may be better suited for accessing data for analytics. Join us in the great SOQL vs. SQL query debate to see which one is best for your analytics project.

SQL vs SOQL for Salesforce Analytics from Sumit Sarkar

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0 Building a Hybrid Data Pipeline for Salesforce and Hadoop /slideshow/building-a-hybrid-data-pipeline-for-salesforce-and-hadoop/76911462 buildingahybriddatapipelineforsalesforceandhadoopfinal-170613181254
My team embarked on building a data lake for our sales and marketing data to better understand customer journeys. This required building a hybrid data pipeline to connect our cloud CRM with the new Hadoop Data Lake. One challenge is that IT was not in a position to provide support until we proved value and marketing did not have the experience, so we embarked on the journey ourselves within the product marketing team for our line of business within Progress. The key to delivering on this was using standard interfaces using a bi-directional data pipeline to connect the systems. On the Salesforce side, we were able to get frictionless access to the data lake using clicks-not-code via OData. On the Hadoop side, we were able to ingest data from Salesforce using JDBC for Apache Sqoop. Join us to hear best practices and lessons learned.]]>
My team embarked on building a data lake for our sales and marketing data to better understand customer journeys. This required building a hybrid data pipeline to connect our cloud CRM with the new Hadoop Data Lake. One challenge is that IT was not in a position to provide support until we proved value and marketing did not have the experience, so we embarked on the journey ourselves within the product marketing team for our line of business within Progress. The key to delivering on this was using standard interfaces using a bi-directional data pipeline to connect the systems. On the Salesforce side, we were able to get frictionless access to the data lake using clicks-not-code via OData. On the Hadoop side, we were able to ingest data from Salesforce using JDBC for Apache Sqoop. Join us to hear best practices and lessons learned.]]> Tue, 13 Jun 2017 18:12:54 GMT /slideshow/building-a-hybrid-data-pipeline-for-salesforce-and-hadoop/76911462 SumitSarkar10@slideshare.net(SumitSarkar10) Building a Hybrid Data Pipeline for Salesforce and Hadoop SumitSarkar10 My team embarked on building a data lake for our sales and marketing data to better understand customer journeys. This required building a hybrid data pipeline to connect our cloud CRM with the new Hadoop Data Lake. One challenge is that IT was not in a position to provide support until we proved value and marketing did not have the experience, so we embarked on the journey ourselves within the product marketing team for our line of business within Progress. The key to delivering on this was using standard interfaces using a bi-directional data pipeline to connect the systems. On the Salesforce side, we were able to get frictionless access to the data lake using clicks-not-code via OData. On the Hadoop side, we were able to ingest data from Salesforce using JDBC for Apache Sqoop. Join us to hear best practices and lessons learned. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/buildingahybriddatapipelineforsalesforceandhadoopfinal-170613181254-thumbnail.jpg?width=120&height=120&fit=bounds" /> My team embarked on building a data lake for our sales and marketing data to better understand customer journeys. This required building a hybrid data pipeline to connect our cloud CRM with the new Hadoop Data Lake. One challenge is that IT was not in a position to provide support until we proved value and marketing did not have the experience, so we embarked on the journey ourselves within the product marketing team for our line of business within Progress. The key to delivering on this was using standard interfaces using a bi-directional data pipeline to connect the systems. On the Salesforce side, we were able to get frictionless access to the data lake using clicks-not-code via OData. On the Hadoop side, we were able to ingest data from Salesforce using JDBC for Apache Sqoop. Join us to hear best practices and lessons learned.

Building a Hybrid Data Pipeline for Salesforce and Hadoop from Sumit Sarkar

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0 Welcome to the Era of Open Analytics /slideshow/welcome-to-the-era-of-open-analytics/76601470 openanalyticscloudexpo-170602191944
Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark. Cloud APIs are commonly designed to support application integration representing a disconnect with the analytics ecosystem. These combined trends create significant demand for a “bring-your-own-analytics” (BYOA) capability for cloud applications. Your cloud may already be smart, but giving users frictionless access to your data will make everyone smarter.]]>
Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark. Cloud APIs are commonly designed to support application integration representing a disconnect with the analytics ecosystem. These combined trends create significant demand for a “bring-your-own-analytics” (BYOA) capability for cloud applications. Your cloud may already be smart, but giving users frictionless access to your data will make everyone smarter.]]> Fri, 02 Jun 2017 19:19:44 GMT /slideshow/welcome-to-the-era-of-open-analytics/76601470 SumitSarkar10@slideshare.net(SumitSarkar10) Welcome to the Era of Open Analytics SumitSarkar10 Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark. Cloud APIs are commonly designed to support application integration representing a disconnect with the analytics ecosystem. These combined trends create significant demand for a “bring-your-own-analytics” (BYOA) capability for cloud applications. Your cloud may already be smart, but giving users frictionless access to your data will make everyone smarter. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/openanalyticscloudexpo-170602191944-thumbnail.jpg?width=120&height=120&fit=bounds" /> Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark. Cloud APIs are commonly designed to support application integration representing a disconnect with the analytics ecosystem. These combined trends create significant demand for a “bring-your-own-analytics” (BYOA) capability for cloud applications. Your cloud may already be smart, but giving users frictionless access to your data will make everyone smarter.

Welcome to the Era of Open Analytics from Sumit Sarkar

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0 Journey to SAS Analytics Grid with SAS, R, Python /slideshow/journey-to-sas-analytics-grid-with-sas-r-python/75621463 sasanalyticsgrid-webinar-170503015235
Big data, compliance and a highly skilled workforce are driving organizations to transform their current analytical infrastructure to deliver enterprise computing environments that can support the latest in data science and analytics practices. SAS remains a popular choice for statistical programming languages, but there is growing demand for R and Python. Data engineers are now being tasked to deliver scalable and highly available computing resources to support analytics for a growing number of users and increasing data volumes while maintaining security for their customers.]]>
Big data, compliance and a highly skilled workforce are driving organizations to transform their current analytical infrastructure to deliver enterprise computing environments that can support the latest in data science and analytics practices. SAS remains a popular choice for statistical programming languages, but there is growing demand for R and Python. Data engineers are now being tasked to deliver scalable and highly available computing resources to support analytics for a growing number of users and increasing data volumes while maintaining security for their customers.]]> Wed, 03 May 2017 01:52:35 GMT /slideshow/journey-to-sas-analytics-grid-with-sas-r-python/75621463 SumitSarkar10@slideshare.net(SumitSarkar10) Journey to SAS Analytics Grid with SAS, R, Python SumitSarkar10 Big data, compliance and a highly skilled workforce are driving organizations to transform their current analytical infrastructure to deliver enterprise computing environments that can support the latest in data science and analytics practices. SAS remains a popular choice for statistical programming languages, but there is growing demand for R and Python. Data engineers are now being tasked to deliver scalable and highly available computing resources to support analytics for a growing number of users and increasing data volumes while maintaining security for their customers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sasanalyticsgrid-webinar-170503015235-thumbnail.jpg?width=120&height=120&fit=bounds" /> Big data, compliance and a highly skilled workforce are driving organizations to transform their current analytical infrastructure to deliver enterprise computing environments that can support the latest in data science and analytics practices. SAS remains a popular choice for statistical programming languages, but there is growing demand for R and Python. Data engineers are now being tasked to deliver scalable and highly available computing resources to support analytics for a growing number of users and increasing data volumes while maintaining security for their customers.

Journey to SAS Analytics Grid with SAS, R, Python from Sumit Sarkar

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0 Journey to Marketing Data Lake [BRK1098] /slideshow/journey-to-marketing-data-lake-brk1098/75109674 oraclemme-final-170418005539
The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098]]>
The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098]]> Tue, 18 Apr 2017 00:55:39 GMT /slideshow/journey-to-marketing-data-lake-brk1098/75109674 SumitSarkar10@slideshare.net(SumitSarkar10) Journey to Marketing Data Lake [BRK1098] SumitSarkar10 The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/oraclemme-final-170418005539-thumbnail.jpg?width=120&height=120&fit=bounds" /> The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098

Journey to Marketing Data Lake [BRK1098] from Sumit Sarkar

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0 REST API debate: OData vs GraphQL vs ORDS /slideshow/rest-api-debate-odata-vs-graphql-vs-ords/73120010 partnersummitrest-api-debate-final-170314061005
Learn the latest industry trends surrounding REST API standardization and what this means for your roadmap. OData is an OASIS standard REST API and has been established among tech companies such as Microsoft, SAP, CA, IBM and Salesforce. GraphQL was created by Facebook in 2015 and has already been deployed at tech companies such as Facebook, Shopify and Intuit. ORDS is the Oracle REST API and delivers similar standardization for Oracle-centric applications.]]>
Learn the latest industry trends surrounding REST API standardization and what this means for your roadmap. OData is an OASIS standard REST API and has been established among tech companies such as Microsoft, SAP, CA, IBM and Salesforce. GraphQL was created by Facebook in 2015 and has already been deployed at tech companies such as Facebook, Shopify and Intuit. ORDS is the Oracle REST API and delivers similar standardization for Oracle-centric applications.]]> Tue, 14 Mar 2017 06:10:05 GMT /slideshow/rest-api-debate-odata-vs-graphql-vs-ords/73120010 SumitSarkar10@slideshare.net(SumitSarkar10) REST API debate: OData vs GraphQL vs ORDS SumitSarkar10 Learn the latest industry trends surrounding REST API standardization and what this means for your roadmap. OData is an OASIS standard REST API and has been established among tech companies such as Microsoft, SAP, CA, IBM and Salesforce. GraphQL was created by Facebook in 2015 and has already been deployed at tech companies such as Facebook, Shopify and Intuit. ORDS is the Oracle REST API and delivers similar standardization for Oracle-centric applications. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/partnersummitrest-api-debate-final-170314061005-thumbnail.jpg?width=120&height=120&fit=bounds" /> Learn the latest industry trends surrounding REST API standardization and what this means for your roadmap. OData is an OASIS standard REST API and has been established among tech companies such as Microsoft, SAP, CA, IBM and Salesforce. GraphQL was created by Facebook in 2015 and has already been deployed at tech companies such as Facebook, Shopify and Intuit. ORDS is the Oracle REST API and delivers similar standardization for Oracle-centric applications.

REST API debate: OData vs GraphQL vs ORDS from Sumit Sarkar

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0 Salesforce Connect External Object Reports /slideshow/salesforce-connect-external-object-reports/70186705 salesforcexreports-final-161215215502
Salesforce shops, including ourselves, have been eagerly anticipating external object support with reports. Starting in Winter ’17, you can build native reports with on-demand access to external data sources such as Oracle, SQL Server, Greenplum, Amazon Redshift, IBM DB2 or Hadoop Big Data Platforms. External objects are powered by Salesforce Connect and provide clicks-not-code data access for admins, devs and general users. But is all of this too good to be true? During this webinar, you’ll learn: - Introduce External Objects and their new capabilities for Reporting and Wave trending in Winter ‘17 - How to setup Salesforce report with external data sources - How to produce OData from warehouses, marts, lakes or other reporting systems. Report considerations and limitations with Salesforce Connect ]]>
Salesforce shops, including ourselves, have been eagerly anticipating external object support with reports. Starting in Winter ’17, you can build native reports with on-demand access to external data sources such as Oracle, SQL Server, Greenplum, Amazon Redshift, IBM DB2 or Hadoop Big Data Platforms. External objects are powered by Salesforce Connect and provide clicks-not-code data access for admins, devs and general users. But is all of this too good to be true? During this webinar, you’ll learn: - Introduce External Objects and their new capabilities for Reporting and Wave trending in Winter ‘17 - How to setup Salesforce report with external data sources - How to produce OData from warehouses, marts, lakes or other reporting systems. Report considerations and limitations with Salesforce Connect ]]> Thu, 15 Dec 2016 21:55:02 GMT /slideshow/salesforce-connect-external-object-reports/70186705 SumitSarkar10@slideshare.net(SumitSarkar10) Salesforce Connect External Object Reports SumitSarkar10 Salesforce shops, including ourselves, have been eagerly anticipating external object support with reports. Starting in Winter ’17, you can build native reports with on-demand access to external data sources such as Oracle, SQL Server, Greenplum, Amazon Redshift, IBM DB2 or Hadoop Big Data Platforms. External objects are powered by Salesforce Connect and provide clicks-not-code data access for admins, devs and general users. But is all of this too good to be true? During this webinar, you’ll learn: - Introduce External Objects and their new capabilities for Reporting and Wave trending in Winter ‘17 - How to setup Salesforce report with external data sources - How to produce OData from warehouses, marts, lakes or other reporting systems. Report considerations and limitations with Salesforce Connect <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/salesforcexreports-final-161215215502-thumbnail.jpg?width=120&height=120&fit=bounds" /> Salesforce shops, including ourselves, have been eagerly anticipating external object support with reports. Starting in Winter ’17, you can build native reports with on-demand access to external data sources such as Oracle, SQL Server, Greenplum, Amazon Redshift, IBM DB2 or Hadoop Big Data Platforms. External objects are powered by Salesforce Connect and provide clicks-not-code data access for admins, devs and general users. But is all of this too good to be true? During this webinar, you’ll learn: - Introduce External Objects and their new capabilities for Reporting and Wave trending in Winter ‘17 - How to setup Salesforce report with external data sources - How to produce OData from warehouses, marts, lakes or other reporting systems. Report considerations and limitations with Salesforce Connect

Salesforce Connect External Object Reports from Sumit Sarkar

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0 Hybrid Data Pipeline for SQL and REST /slideshow/hybrid-data-pipeline-for-sql-and-rest/68605616 hdpwebinarpresentationdraft1109-161110192238
Completely transform the way Cloud apps access data Progress® DataDirect® Hybrid Data Pipeline is the industry’s first hybrid data pipeline that can run independently and integrate with any single or multi-vendor technology stack connected by open standards for SQL and REST.]]>
Completely transform the way Cloud apps access data Progress® DataDirect® Hybrid Data Pipeline is the industry’s first hybrid data pipeline that can run independently and integrate with any single or multi-vendor technology stack connected by open standards for SQL and REST.]]> Thu, 10 Nov 2016 19:22:37 GMT /slideshow/hybrid-data-pipeline-for-sql-and-rest/68605616 SumitSarkar10@slideshare.net(SumitSarkar10) Hybrid Data Pipeline for SQL and REST SumitSarkar10 Completely transform the way Cloud apps access data Progress® DataDirect® Hybrid Data Pipeline is the industry’s first hybrid data pipeline that can run independently and integrate with any single or multi-vendor technology stack connected by open standards for SQL and REST. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hdpwebinarpresentationdraft1109-161110192238-thumbnail.jpg?width=120&height=120&fit=bounds" /> Completely transform the way Cloud apps access data Progress® DataDirect® Hybrid Data Pipeline is the industry’s first hybrid data pipeline that can run independently and integrate with any single or multi-vendor technology stack connected by open standards for SQL and REST.

Hybrid Data Pipeline for SQL and REST from Sumit Sarkar

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0 Firewall friendly pipeline for secure data access /slideshow/firewall-friendly-pipeline-for-secure-data-access/67021242 firewallfriendlywebinarslidedeck-slideshare-161011171002
Learn how to access data over standard SQL or REST directly in the cloud or behind a firewall.]]>
Learn how to access data over standard SQL or REST directly in the cloud or behind a firewall.]]> Tue, 11 Oct 2016 17:10:02 GMT /slideshow/firewall-friendly-pipeline-for-secure-data-access/67021242 SumitSarkar10@slideshare.net(SumitSarkar10) Firewall friendly pipeline for secure data access SumitSarkar10 Learn how to access data over standard SQL or REST directly in the cloud or behind a firewall. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/firewallfriendlywebinarslidedeck-slideshare-161011171002-thumbnail.jpg?width=120&height=120&fit=bounds" /> Learn how to access data over standard SQL or REST directly in the cloud or behind a firewall.

Firewall friendly pipeline for secure data access from Sumit Sarkar

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0 Salesforce External Objects for Big Data /slideshow/salesforce-external-objects-for-big-data/66748160 df16-bigdata-161005045443
Transform Salesforce into the system of engagement for your big data. Discuss best practices and lessons learned in accessing external data sets in Hadoop or Spark using Salesforce Connect. Leave the big data sets behind the firewall, and get on demand access for your users to big data insights using external objects with Salesforce Connect. In this session we will cover: Intro to Salesforce Connect Intro to Big Data Landscape How to connect Salesforce to Big Data using External Data Sources Lessons Learned accessing Big Data using External Objects for native reporting, writes, lookups, search and more Resources (How to learn more)]]>
Transform Salesforce into the system of engagement for your big data. Discuss best practices and lessons learned in accessing external data sets in Hadoop or Spark using Salesforce Connect. Leave the big data sets behind the firewall, and get on demand access for your users to big data insights using external objects with Salesforce Connect. In this session we will cover: Intro to Salesforce Connect Intro to Big Data Landscape How to connect Salesforce to Big Data using External Data Sources Lessons Learned accessing Big Data using External Objects for native reporting, writes, lookups, search and more Resources (How to learn more)]]> Wed, 05 Oct 2016 04:54:43 GMT /slideshow/salesforce-external-objects-for-big-data/66748160 SumitSarkar10@slideshare.net(SumitSarkar10) Salesforce External Objects for Big Data SumitSarkar10 Transform Salesforce into the system of engagement for your big data. Discuss best practices and lessons learned in accessing external data sets in Hadoop or Spark using Salesforce Connect. Leave the big data sets behind the firewall, and get on demand access for your users to big data insights using external objects with Salesforce Connect. In this session we will cover: Intro to Salesforce Connect Intro to Big Data Landscape How to connect Salesforce to Big Data using External Data Sources Lessons Learned accessing Big Data using External Objects for native reporting, writes, lookups, search and more Resources (How to learn more) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/df16-bigdata-161005045443-thumbnail.jpg?width=120&height=120&fit=bounds" /> Transform Salesforce into the system of engagement for your big data. Discuss best practices and lessons learned in accessing external data sets in Hadoop or Spark using Salesforce Connect. Leave the big data sets behind the firewall, and get on demand access for your users to big data insights using external objects with Salesforce Connect. In this session we will cover: Intro to Salesforce Connect Intro to Big Data Landscape How to connect Salesforce to Big Data using External Data Sources Lessons Learned accessing Big Data using External Objects for native reporting, writes, lookups, search and more Resources (How to learn more)

Salesforce External Objects for Big Data from Sumit Sarkar

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0 OData Hackathon Challenge /slideshow/odata-hackathon-challenge/65913058 integrate-hackathon-160911201454
First OData hackathon challenge at Integrate+API World Challenge using NLP and interoperability against multiple CRM data sources]]>
First OData hackathon challenge at Integrate+API World Challenge using NLP and interoperability against multiple CRM data sources]]> Sun, 11 Sep 2016 20:14:54 GMT /slideshow/odata-hackathon-challenge/65913058 SumitSarkar10@slideshare.net(SumitSarkar10) OData Hackathon Challenge SumitSarkar10 First OData hackathon challenge at Integrate+API World Challenge using NLP and interoperability against multiple CRM data sources <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/integrate-hackathon-160911201454-thumbnail.jpg?width=120&height=120&fit=bounds" /> First OData hackathon challenge at Integrate+API World Challenge using NLP and interoperability against multiple CRM data sources

OData Hackathon Challenge from Sumit Sarkar

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0 OData and the future of business objects universes /slideshow/odata-and-the-future-of-business-objects-universes/63350503 odataandthefutureofbusinessobjectsuniverses-160622193740
Presentation to walk through OData ecosystem for SAP BO shops looking to maximize investment in their universe.]]>
Presentation to walk through OData ecosystem for SAP BO shops looking to maximize investment in their universe.]]> Wed, 22 Jun 2016 19:37:40 GMT /slideshow/odata-and-the-future-of-business-objects-universes/63350503 SumitSarkar10@slideshare.net(SumitSarkar10) OData and the future of business objects universes SumitSarkar10 Presentation to walk through OData ecosystem for SAP BO shops looking to maximize investment in their universe. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/odataandthefutureofbusinessobjectsuniverses-160622193740-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation to walk through OData ecosystem for SAP BO shops looking to maximize investment in their universe.

OData and the future of business objects universes from Sumit Sarkar

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0 Building a marketing data lake /slideshow/building-a-marketing-data-lake/61204452 webinar-marketing-data-lakes-160421180649
How ISVs are ingesting marketing data from different sources such as Salesforce, Eloqua, Marketo, Google Analytics, Omniture and more.]]>
How ISVs are ingesting marketing data from different sources such as Salesforce, Eloqua, Marketo, Google Analytics, Omniture and more.]]> Thu, 21 Apr 2016 18:06:49 GMT /slideshow/building-a-marketing-data-lake/61204452 SumitSarkar10@slideshare.net(SumitSarkar10) Building a marketing data lake SumitSarkar10 How ISVs are ingesting marketing data from different sources such as Salesforce, Eloqua, Marketo, Google Analytics, Omniture and more. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinar-marketing-data-lakes-160421180649-thumbnail.jpg?width=120&height=120&fit=bounds" /> How ISVs are ingesting marketing data from different sources such as Salesforce, Eloqua, Marketo, Google Analytics, Omniture and more.

Building a marketing data lake from Sumit Sarkar

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0 OData External Data Integration Strategies for SaaS /slideshow/odata-external-data-integration-strategies-for-saas/58855961 odata-for-saas-data-strategies-160229141145
OData External Data Integration Strategies for SaaS]]>
OData External Data Integration Strategies for SaaS]]> Mon, 29 Feb 2016 14:11:44 GMT /slideshow/odata-external-data-integration-strategies-for-saas/58855961 SumitSarkar10@slideshare.net(SumitSarkar10) OData External Data Integration Strategies for SaaS SumitSarkar10 OData External Data Integration Strategies for SaaS <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/odata-for-saas-data-strategies-160229141145-thumbnail.jpg?width=120&height=120&fit=bounds" /> OData External Data Integration Strategies for SaaS

OData External Data Integration Strategies for SaaS from Sumit Sarkar

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0 Webinar on MongoDB BI Connectors /slideshow/webinar-on-mongodb-bi-connectors/58717548 webinar-mongodb-bi-connectors-160225163823
Discuss certified BI Connector options from MongoDB and Progress DataDirect, with a real world JDBC demo from Tibco Jaspersoft]]>
Discuss certified BI Connector options from MongoDB and Progress DataDirect, with a real world JDBC demo from Tibco Jaspersoft]]> Thu, 25 Feb 2016 16:38:23 GMT /slideshow/webinar-on-mongodb-bi-connectors/58717548 SumitSarkar10@slideshare.net(SumitSarkar10) Webinar on MongoDB BI Connectors SumitSarkar10 Discuss certified BI Connector options from MongoDB and Progress DataDirect, with a real world JDBC demo from Tibco Jaspersoft <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinar-mongodb-bi-connectors-160225163823-thumbnail.jpg?width=120&height=120&fit=bounds" /> Discuss certified BI Connector options from MongoDB and Progress DataDirect, with a real world JDBC demo from Tibco Jaspersoft

Webinar on MongoDB BI Connectors from Sumit Sarkar

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0 Lightning Connect: Lessons Learned /slideshow/lightning-connect-lessons-learned/53471144 df15-lightningconnectin5dayslessonslearned-notes-151002164245-lva1-app6891
Dreamforce '15 Devzone slides for Day POC on Lightning Connect and Lessons Learned.]]>
Dreamforce '15 Devzone slides for Day POC on Lightning Connect and Lessons Learned.]]> Fri, 02 Oct 2015 16:42:45 GMT /slideshow/lightning-connect-lessons-learned/53471144 SumitSarkar10@slideshare.net(SumitSarkar10) Lightning Connect: Lessons Learned SumitSarkar10 Dreamforce '15 Devzone slides for Day POC on Lightning Connect and Lessons Learned. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/df15-lightningconnectin5dayslessonslearned-notes-151002164245-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Dreamforce '15 Devzone slides for Day POC on Lightning Connect and Lessons Learned.

Lightning Connect: Lessons Learned from Sumit Sarkar

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0 Ibis 2015 final template /slideshow/ibis-2015-final-template/49744453 ibis2015finaltemplate-150623163852-lva1-app6892
Create SAP Business Objects Cloud Universe such as Salesforce, NetSuite, ServiceNow, Eloqua, Marketo, Google Analytics, etc.]]>
Create SAP Business Objects Cloud Universe such as Salesforce, NetSuite, ServiceNow, Eloqua, Marketo, Google Analytics, etc.]]> Tue, 23 Jun 2015 16:38:52 GMT /slideshow/ibis-2015-final-template/49744453 SumitSarkar10@slideshare.net(SumitSarkar10) Ibis 2015 final template SumitSarkar10 Create SAP Business Objects Cloud Universe such as Salesforce, NetSuite, ServiceNow, Eloqua, Marketo, Google Analytics, etc. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ibis2015finaltemplate-150623163852-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Create SAP Business Objects Cloud Universe such as Salesforce, NetSuite, ServiceNow, Eloqua, Marketo, Google Analytics, etc.

Ibis 2015 final template from Sumit Sarkar

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0 https://cdn.slidesharecdn.com/profile-photo-SumitSarkar10-48x48.jpg?cb=1585050643 Data Access Evangelist, Speaker and industry expert on open data standards connectivity with Cloud Data. Sumit Sarkar has been working in the data connectivity field for over 10 years. His interests include performance tuning of the data access layer for which he has developed a patent pending technology for its analysis; and data connectivity and ingestion for analytics with data of all shapes and sizes in the cloud or ground with a focus on standards such as ODBC, JDBC, ADO.NET, GraphQL and OData. He is an IBM Certified Consultant for IBM Cognos Business Intelligence and TDWI member. He has presented sessions on data connectivity at various conferences including IUC34, IUC35, Progre... https://cdn.slidesharecdn.com/ss_thumbnails/whatserverlessmeansforenterpriseapps-campit-181115030147-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/what-serverless-means-for-enterprise-apps/123048455 What serverless means ... https://cdn.slidesharecdn.com/ss_thumbnails/idevnews-webinar-mobility-final-180518183121-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/digitize-enterprise-assets-for-mobility/97528883 Digitize Enterprise As... https://cdn.slidesharecdn.com/ss_thumbnails/apiworldstage2017-170927153840-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/data-apis-dont-discriminate-api-world-stage-talk/80221580 Data APIs Don't Discri...