Business Performance (BPI) Network: Reports

Report

Id: 79
Date
Title: Bringing Simplicity to Multi-Cloud Complexity
Summary: Organizations worldwide are struggling to turn growing volumes of structured and unstructured data into readily available decision support for meaningful insights and actions.
Author: BPI Network
Body: Chief Data Officers and IT leaders are grappling with a host of challenges as they seek to modernize data infrastructures and locate, unify and leverage data assets. Nonetheless, they are making significant progress in their efforts to realize greater value from growing cloud-based data repositories. A new report, “Bringing Simplicity to Multi-Cloud Complexity: Advancing Data Connectivity, Logistics and Value,” finds that organizations worldwide are struggling to turn growing volumes of structured and unstructured data into readily available decision support for meaningful insights and actions.  The report from the Business Performance Innovation (BPI) Network is based on interviews with nearly 20 CDOs and cloud experts from organizations like NRG Energy, Commerzbank, Morningstar, Thrivent, Etsy, Deloitte, Cognizant, IBM, Pure Storage, TIBCO, Teradata, and QuaXigma. Opinions reveal most enterprises are still early in their journey, as they work to resolve critical logistical issues and bottlenecks in simplifying and improving the quality, visibility, synchronization, replication and migration of data across hybrid and multi-cloud environments.
Image: Cover Thumbnail.png
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Created: 2020-10-19 15:09:05
Modified: 2024-10-16 21:07:33

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Id	Title	Subtitle	Description	Date	Created	Modified	Actions
31	Bringing Simplicity To Multi-Cloud Complexity	Advancing Data Connectivity, Logistics and Value	Overview The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity. While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value. The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world. Background The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments. Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences. Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially. According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015. In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy. In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds. Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity. For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality. Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world. To get involved in this initiative, please reach out to Dave Murray.	2020-08-12	2020-08-11 21:56:11	2020-08-14 18:49:19	View Edit Delete

Title

Subtitle

Description

Date

Created

Modified

Actions

Bringing Simplicity To Multi-Cloud Complexity

Advancing Data Connectivity, Logistics and Value

Overview

The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity.

While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value.

The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world.

Background

The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments.

Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences.

Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially. According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015.

In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy.

In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds.

Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats.

It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge.

The Data Logistics Mandate

In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs.

Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements.

Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data.

For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity.

For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality.

Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world.

To get involved in this initiative, please reach out to Dave Murray.

2020-08-12

2020-08-11 21:56:11

2020-08-14 18:49:19

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 bodyChief Data Officers and IT leaders are grappling with a host of challenges as they seek to modernize data infrastructures and locate, unify and leverage data assets. Nonetheless, they are making significant progress in their efforts to realize greater value from growing cloud-based data repositories. A new report, “Bringing Simplicity to Multi-Cloud Complexity: Advancing Data Connectivity, Logistics and Value,” finds that organizations worldwide are struggling to turn growing volumes of structured and unstructured data into readily available decision support for meaningful insights and actions. The report from the Business Performance Innovation (BPI) Network is based on interviews with nearly 20 CDOs and cloud experts from organizations like NRG Energy, Commerzbank, Morningstar, Thrivent, Etsy, Deloitte, Cognizant, IBM, Pure Storage, TIBCO, Teradata, and QuaXigma. Opinions reveal most enterprises are still early in their journey, as they work to resolve critical logistical issues and bottlenecks in simplifying and improving the quality, visibility, synchronization, replication and migration of data across hybrid and multi-cloud environments.
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 descriptionOverview The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity. While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value. The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world. Background The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments. Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences. Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially. According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015. In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy. In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds. Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity. For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality. Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world. 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Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences. Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially. According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015. In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy. In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds. Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity. For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality. Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world. 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Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value. The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world. Background The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments. 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According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy. In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds. Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. 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To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. 
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Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity. For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality. Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world. 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Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value. The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world. Background The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments. Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences. Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially. According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015. In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy. In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds. Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats. It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge. The Data Logistics Mandate In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs. Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements. Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data. For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. 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To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. 
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 id5
 titleBusiness Volatility & Variables
 subtitle
 summaryAdaptive Planning and The BPI Network bring you a quarterly pulse of financial professionals on current economic conditions, the impact on corporate performance and plans, and the effectiveness of financial management practices in uncertain times.
 descriptionAdaptive Planning and The BPI Network bring you a quarterly pulse of financial professionals on current economic conditions, the impact on corporate performance and plans, and the effectiveness of financial management practices in uncertain times.
 imagebpi-6.jpg
 thumbnail
 date2013-10-08
 feature(false)
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 created2013-10-06 12:58:05
 modified2014-07-29 17:00:40
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- signedin_user_id(null)
- signedin_user_email(null)
- answerEncryptedIiwzLGAKYAo=
- questionEncryptedOjUmQUUoJllFPicwQDtHNU04RjVSKCYlRj0mNVIoIyRSKCNcYApgCg==
- pageTitleBusiness Performance & Innovation (BPI) Network
- $request->data(empty)
- $this->validationErrors
 Menu(empty)
 User(empty)
 Article(empty)
 Event(empty)
 Report(empty)
 Leader(empty)
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 ArticlesProgram(empty)
 ArticlesLeader(empty)
 Tag(empty)
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 Brainwafe(empty)
 BrainwavesEvent(empty)
 EventsProgram(empty)
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 Download(empty)
 ProgramsReport(empty)
 ReportsTag(empty)
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 MediaCoverageReport(empty)
 BrainwavesReport(empty)
- Loaded Helpers
 0Minify
 1Number
 2SimpleGraph
 3DebugTimer
 4Toolbar
 5Html
 6Form
 7Session
 8HtmlToolbar
====

Environment

App Constants

No application environment available.

CakePHP Constants

Constant	Value
APP	/home/bpinorg/public_html/app/
APP_DIR	app
APPLIBS	/home/bpinorg/public_html/app/Lib/
CACHE	/home/bpinorg/public_html/app/tmp/cache/
CAKE	/home/bpinorg/public_html/lib/Cake/
CAKE_CORE_INCLUDE_PATH	/home/bpinorg/public_html/lib
CORE_PATH	/home/bpinorg/public_html/lib/
CAKE_VERSION	2.3.8
CSS	/home/bpinorg/public_html/app/webroot/css/
CSS_URL	css/
DS	/
FULL_BASE_URL	https://bpinetwork.org
IMAGES	/home/bpinorg/public_html/app/webroot/img/
IMAGES_URL	img/
JS	/home/bpinorg/public_html/app/webroot/js/
JS_URL	js/
LOGS	/home/bpinorg/public_html/app/tmp/logs/
ROOT	/home/bpinorg/public_html
TESTS	/home/bpinorg/public_html/app/Test/
TMP	/home/bpinorg/public_html/app/tmp/
VENDORS	/home/bpinorg/public_html/vendors/
WEBROOT_DIR	webroot
WWW_ROOT	/home/bpinorg/public_html/app/webroot/

PHP Environment

Environment Variable	Value
Php Version	5.6.40
User	bpinorg
Home	/home/bpinorg
Fcgi Role	RESPONDER
Redirect Redirect Unique Id	aBDAm_GG-mHoWABqvk0XVwABTwA
Redirect Redirect Script Url	/reports/view/79
Redirect Redirect Script Uri	https://bpinetwork.org/reports/view/79
Redirect Redirect Https	on
Redirect Redirect Ssl Tls Sni	bpinetwork.org
Redirect Redirect Http2	on
Redirect Redirect H2push	off
Redirect Redirect H2 Push	off
Redirect Redirect H2 Pushed
Redirect Redirect H2 Pushed On
Redirect Redirect H2 Stream Id	1
Redirect Redirect H2 Stream Tag	17553-0-1
Redirect Redirect Status	200
Redirect Unique Id	aBDAm_GG-mHoWABqvk0XVwABTwA
Redirect Script Url	/reports/view/79
Redirect Script Uri	https://bpinetwork.org/reports/view/79
Redirect Https	on
Redirect Ssl Tls Sni	bpinetwork.org
Redirect Http2	on
Redirect H2push	off
Redirect H2 Push	off
Redirect H2 Pushed
Redirect H2 Pushed On
Redirect H2 Stream Id	1
Redirect H2 Stream Tag	17553-0-1
Redirect Status	200
Unique Id	aBDAm_GG-mHoWABqvk0XVwABTwA
Script Url	/reports/view/79
Script Uri	https://bpinetwork.org/reports/view/79
Https	on
Ssl Tls Sni	bpinetwork.org
Http2	on
H2push	off
H2 Push	off
H2 Pushed
H2 Pushed On
H2 Stream Id	1
H2 Stream Tag	17553-0-1
Proxy-nokeepalive	1
Http Accept	/
Http User Agent	Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
Http Accept Encoding	gzip, br, zstd, deflate
Http Host	bpinetwork.org
Http X Https	1
Path	/usr/local/jdk/bin:/usr/kerberos/sbin:/usr/kerberos/bin:/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/usr/X11R6/bin:/usr/local/bin:/usr/X11R6/bin:/root/bin:/opt/bin
Server Signature
Server Software	Apache
Server Name	bpinetwork.org
Server Addr	173.231.198.134
Server Port	443
Remote Addr	3.14.247.147
Document Root	/home/bpinorg/public_html
Request Scheme	https
Context Prefix
Context Document Root	/home/bpinorg/public_html
Server Admin	webmaster@bpinetwork.org
Script Filename	/home/bpinorg/public_html/app/webroot/index.php
Remote Port	51271
Redirect Url	/app/webroot/reports/view/79
Gateway Interface	CGI/1.1
Server Protocol	HTTP/2.0
Request Method	GET
Query String
Request Uri	/reports/view/79
Script Name	/app/webroot/index.php
Php Self	/app/webroot/index.php
Request Time Float	1745928347.8057
Request Time	1745928347
Argc	0

====

Include
+
Included Files

Include Paths
- 0/home/bpinorg/public_html/lib
- 2/opt/cpanel/ea-php56/root/usr/share/pear
- 3-> /home/bpinorg/public_html/lib/Cake/
Included Files
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  Controller
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  1CORE/Controller/ComponentCollection.php
  2CORE/Controller/Component.php
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  1CORE/I18n/L10n.php
  Log
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  6CORE/Routing/Route/RedirectRoute.php
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  4CORE/Utility/ClassRegistry.php
  5CORE/Utility/Inflector.php
  6CORE/Utility/Folder.php
  View
  0CORE/View/HelperCollection.php
- app
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  Config
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  2APP/Config/routes.php
  3APP/Config/database.php
  Controller
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  1APP/Controller/AppController.php
  Model
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  1APP/Model/AppModel.php
  2APP/Model/User.php
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  5APP/Model/Report.php
  6APP/Model/Leader.php
  7APP/Model/Program.php
  8APP/Model/Tag.php
  9APP/Model/Brainwafe.php
  10APP/Model/Tracking.php
  11APP/Model/Download.php
  12APP/Model/MediaCoverage.php
  Other
  0APP/webroot/index.php
  1APP/Lib/AppError.php
  2APP/Vendor/ChromePhp/ChromePhp.php
  3APP/Lib/Captcha/Captcha.php
- plugins
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  Component
  0CsvView/Controller/Component/CsvViewComponent.php
  DebugKit
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  Plugin
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  1DebugKit/Lib/Panel/HistoryPanel.php
  2DebugKit/Lib/DebugPanel.php
  3DebugKit/Lib/Panel/SessionPanel.php
  4DebugKit/Lib/Panel/RequestPanel.php
  5DebugKit/Lib/Panel/SqlLogPanel.php
  6DebugKit/Lib/Panel/TimerPanel.php
  7DebugKit/Lib/Panel/LogPanel.php
  8DebugKit/Lib/Log/Engine/DebugKitLog.php
  9DebugKit/Lib/Panel/VariablesPanel.php
  10DebugKit/Lib/Panel/EnvironmentPanel.php
  11DebugKit/Lib/Panel/IncludePanel.php
  12DebugKit/Lib/DebugTimer.php
  LessCompiler
  Component
  0LessCompiler/Controller/Component/LessComponent.php
  Plugin
  0LessCompiler/Lib/LessCompiler.php
  1LessCompiler/Vendor/lessc.php
  Minify
  Config
  0Minify/Config/routes.php
  Opauth
  Config
  0Opauth/Config/bootstrap.php
  1Opauth/Config/routes.php
====

Business Performance (BPI) Network

Report

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Request History

Session

Request

Cake Params

Post data

Query string

Cookie

Current Route

Sql Logs

default

Total Time: 5 ms Total Queries: 28 queries

Query Explain:

Memory

Timers

Logs

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App Constants

CakePHP Constants

PHP Environment

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Included Files

Total Time: 5 ms
Total Queries: 28 queries