Deriving Value from your Stored Data by Using Innovative Pricing Schemes

Transcription

1 Deriving Value from your Stored Data by Using Innovative Pricing Schemes How Businesses Can Benefit from IBM s Innovative Pricing and Architecture A Frost & Sullivan Executive Brief SPONSORED BY IBM

2 Frost & Sullivan Introduction...3 Why Traditional Storage Tiers are Unsuitable for Unpredictable Data Needs...4 Innovative Pricing and Architecture Drive Flexibility in IBM Cloud Object Storage...5 Tiering...5 High Availability/Accessibility of Data...6 Use Cases...6 Innovation Labs/Sandbox...7 Cost-effective Access for Enterprise-wide Data...7 Using Archived Data for Medical Break-throughs...7 Keeping up with IOT and Variable Workloads...8 Leveraging Fickle Customer Data to Derive New Insights...8 Better Data Access in Time of Crisis...8 Bottom Line: Cost Comparisons for Storage Workloads in IBM Cloud Object Storage Flex Option, Amazon S3, and Azure Blob Storage...9 Sample Case Study Parameters...9 Competitive Pricing Scenarios...9 Conclusion...12 CONTENTS

3 INTRODUCTION In the digital era, data is king. Businesses are looking to extract value from both proprietary and publicly available data, via sophisticated analytics and artificial intelligence software. The insights they derive support key strategic priorities, including market growth, increased productivity, and innovation. In fact, 54% of CEOs worldwide surveyed by Frost & Sullivan say they expect intelligent data analytics to be the key driver for growth in their business. 1 With analytics becoming a strategic imperative for competitive differentiation, businesses are collecting, retaining, and processing more data, of more types, for longer periods of time. They must protect their valuable data assets through replication across data centers and regions. Furthermore, their data needs are unpredictable; they cannot necessarily know in advance when and how frequently they will need to access the data they collect. For IT leaders, the challenge is not simply finding available capacity, but also ensuring that the business can continually derive value from it. Forty-one percent of IT decision-makers surveyed by Frost & Sullivan expressed concerned that they have too much data and not enough knowledge of what to do with it. 2 54% of CEOs worldwide say they expect intelligent data analytics to be the key driver for growth in their business. Most of the data enterprises are collecting is not being exposed to next-generation analytics and collaboration tools. Experts estimate that only 1% of the vast amounts of data generated has been analyzed. 3 Part of the reason for the gap is that the stored data cannot be easily accessed, searched, or analyzed by the applications or workgroups that could benefit from it. To be sure that they are developing and executing a storage strategy that will support business success into the future, enterprises need to re-think how their employees can extract more value from stored data; and select the storage provider that can best help them meet their goals. In this paper, we look at an innovative storage paradigm introduced by IBM. We consider how workloads with unpredictable access patterns can benefit from IBM s flexible, accessible, and cost-effective Cloud Object Storage Flex offering, for better analytics and collaboration. Finally, we compare pricing for equivalent workloads across leading services Amazon S3, Azure Blob, and IBM Cloud Object Storage Flex showing that the unique architecture and service parameters of IBM Cloud Object Storage Flex can translate to lower overall costs and greater business value. 1 Frost & Sullivan, CEOs Perspective on Growth, Innovation, and Leadership, Frost & Sullivan, Big Data & Analytics Survey, McKinsey, McKinsey Quarterly, Straight talk about big data (September 2016), digital-mckinsey/our-insights/straight-talk-about-big-data. All rights reserved 2017 Frost & Sullivan 3

4 WHY TRADITIONAL STORAGE TIERS ARE UNSUITABLE FOR UNPREDICTABLE DATA NEEDS Traditional storage systems rely on data tiering, a traditional approach that requires businesses to rank data based on how often data is likely to be accessed. Most cloud storage providers offer two or three standard tiers of service, as follows: Storage Tier Hot Cool Typical Data Type Most recent, more critical or valuable data Aging and less critical data Data Access Frequency High (e.g., daily, weekly) Lower (e.g., monthly, quarterly) Storage Costs High Mid-range Data Retrieval Costs Low High Cold Archival, oldest and least valuable data Lowest (e.g., annually or rarely) Low High plus longer access times When data access needs are variable, tiered storage presents several challenges to storage professionals and the business: Predicting the unpredictable: Storage teams must predict data value and frequency of access, so that they can find the right cost vs. access model. And moving data across tiers generally requires paying for automation tools. Without such tools, a wrong prediction or an urgent business event can impact cost, time-to-access, application performance, and ultimately, the value to the organization. Cost vs. immediacy: When the value of data is evolving, expanding and unpredictable, the business either risks paying too much to store and retrieve its data, or risks not having immediate access at critical and strategic times. For example, a broadcast news service searching through archival footage to enhance breaking news may miss the competitive window for being first to market with unique content. Budget challenges: When cold data is accessed frequently, high data retrieval costs can wreak havoc with budgets, and create unpredictable budget fluctuations, making it difficult for IT leaders to effectively manage their resources. Data longevity: Businesses are starting to leverage long-archived data, to understand trends and to uncover new insights. Thirty-nine percent of businesses surveyed by Frost & Sullivan say they are using analytics tools to investigate and better utilize existing data that may stretch back years. 4 To derive value from these assets, IT leaders need to ensure that even cold data is easily and quickly accessible. The traditional tiered storage approach may not be flexible enough for evolving enterprise needs, including: escalating access demands the extended length of time data remains valuable the increasing unpredictability of workloads requiring access the desire for innovation through data analytics and experimentation 4 Frost & Sullivan Big Data & Analytics Survey, All rights reserved 2017 Frost & Sullivan

5 Today s expectations for collaboration add to the unpredictable demand for data access. Data is being repurposed and shared across teams. This means that a wider range of data must be available and accessible to diverse groups of employees and partners, who may need it at any time, and often on a global basis. Ironically, at a time when businesses are collecting vast quantities of data on which to run analytics, and are eager to share data across collaborative work groups, the traditional (and more rigid) tiered cloud storage structure may inadvertently restrict the free flow of data, due to budget constraints. In effect, high retrieval costs can discourage the use of cold data, thus stifling analysis, collaboration, and innovation efforts. And if too much of the budget is spent paying for hot data that isn t accessed frequently, the IT budget is constrained all the more. What businesses need is a new type of cloud object storage designed for the data-aware and data-dependent future, such as IBM Cloud Object Storage and its new Flex pricing option. INNOVATIVE PRICING AND ARCHITECTURE DRIVE FLEXIBILITY IN IBM CLOUD OBJECT STORAGE All cloud object storage services are not alike; and some of the leading services are not designed to deliver on critical needs. To make the optimal choice, enterprises need to do their due diligence to understand the differences between services and how those differences impact what they pay for cloud storage. In this section, we compare important features of leading services, and show how IBM Cloud Object Storage may best meet the needs of enterprises. Tiering Amazon Web Services and Microsoft Azure require customers to pre-determine a specific pricing tier for all cloud object storage workloads. As noted, this places the onus on enterprise customers to estimate usage accurately or risk paying more and/or incurring delays to access stored data. Such policies don t always allow for the choice and flexibility that clients need today. IBM Cloud Object Storage offers enterprises the flexibility to meet unpredictable business needs. Like many cloud service providers, IBM offers tiered services (Standard, Vault, Cold Vault) that are appropriate when you are confident you know how the data will be used in the future, and how frequently it will be accessed. Recently, IBM announced an innovative new pricing option called Flex, which removes the need to predict usage altogether. Designed for dynamic or unpredictable workloads, all data in this tier is stored at a low price (roughly equivalent to competitors cool tier pricing). To keep budgets more predictable and ensure lowest possible costs, no matter how much the data is used, IBM has implemented a price cap: a maximum charge for combined storage and retrieval, per GB of data. The charge varies for regional and cross-regional storage, so that an enterprise can choose the data resiliency level needed. With the value of data rising, more customers are choosing higher resiliency levels to protect their investments. The following chart shows how IBM s new Flex option compares with traditional cloud storage tiers. All rights reserved 2017 Frost & Sullivan 5

6 Storage Tier Typical Data Type Data Access Frequency Storage Costs Data Retrieval Costs Hot Cool Cold IBM Cloud Object Storage Flex Most recent, more critical or valuable data Aging and less critical data Archive, oldest and least valuable data Unpredictable workloads; value of data is unknown and evolving High (e.g., daily/weekly) Lower (e.g., monthly, quarterly) Lowest (e.g., annually or rarely) Unpredictable or high High Lower Low Mid/low Low High High plus longer access times Capped to encourage data access The unique pricing scheme of IBM Cloud Object Storage Flex meets the needs of enterprises that want the freedom to use intelligence functionality to explore all data regardless of age or assumed value. The pricing cap frees enterprise data analysts and line-of-business employees to entertain what if scenarios, to push the boundaries of the expected; and to uncover previously undiscovered correlations, build intelligent systems, leverage past data to predict future results, react quickly to urgent data needs, and encourage collaboration on a global basis. High Availability/Accessibility of Data Most cloud service providers, including AWS and Azure, tout their cloud object storage services as an easy way for businesses to gain vast amounts of storage capacity. In fact, their capacity-based offerings appear to encourage enterprises to purchase as much capacity as possible: both AWS and Azure recommend that enterprises that want greater resilience should buy capacity in at least two separate geographies (thus increasing the service charges), and then pay to replicate the data across the regions. With IBM Cloud Object Storage, all data is highly accessible, available, and consistent. IBM Cloud Object Storage is designed to support high resilience, with cross-regional data accessibility without charging to replicate storage in multiple regions. In addition, with the Flex offering, all data is quickly available for use, with fast access times. This means you can activate colder data quickly, without a cost penalty. USE CASES Thanks to its innovative pricing structure, IBM Cloud Object Storage Flex offers tremendous advantages for companies that want to utilize data more pro-actively throughout their enterprises, but find it challenging to accurately predict which data sets will be accessed over time. As businesses adopt more agile and collaborative work teams, including external partner organizations and global regions, IT leaders can use the Flex offering to help business units uncover new value and insights from data, without incurring a spike in their budget. Examples of vertical and horizontal use cases include the following. 6 All rights reserved 2017 Frost & Sullivan

7 Innovation Labs/Sandbox Industry: All Companies that prize innovation are supporting innovation labs and sandboxes that allow software developers, business analysts, and other employees and partners to collaborate and play out what if scenarios, using data and artificial intelligence. Such firms understand that when you don t know what data will be useful, all data needs to be available. In fact, 53% of large businesses surveyed by Frost & Sullivan say the best way to find value in Big Data and analytics is to let data analysts and data scientists explore all the data, on their own or in a data sandbox. Sixty percent agree that the more data you have, the more obvious and self-evident the findings will be. 5 With IBM Cloud Object Storage Flex, all data is available to employees and dispersed workgroups without restriction, and while protecting the budget. Businesses that cannot transform to become agile, innovative, and data-reliant may find themselves losing ground to competitors. Cost-effective Access for Enterprise-wide Data Industry: All A corporate communications department is looking to increase its use of video and images for communications with customers, partners, employees, and influencers. Its extensive and growing library of capacity-hungry media assets was formerly archived in difficult-to-access tape, which restricted its usefulness. By migrating its content library to IBM Cloud Object Storage Flex, the organization will make its media assets easily accessible, at a reasonable cost, to diverse users. Product management, customer care, sales, marketing and investor relations, as well as partners, will be able to utilize the media content for uses such as help desk, training videos, social media, press announcements. Benefits include greater asset use, employee productivity, collaboration, partner support, and customer satisfaction. Using Archived Data for Medical Break-throughs Industry: Genomics and research Genome sequencing costs have come down exponentially in the last ten years. As a result, today, a life sciences firm is able to obtain vast amounts of DNA sequencing data for research, to find a cure for a rare disease. Unsure when the data will be needed for various projects, and wanting to capture as much data as possible to build successful models, the firm decides to archive the mountains of genome sequencing data in IBM Cloud Object Storage Flex. Despite the unpredictable access patterns by researchers across the globe, when the firm needs to access the data to run analytics against petabytes of content, it can do so easily without paying exorbitant prices. By increasing the amount of data available for research, and improving the level of real-time collaboration by researchers across the globe, important therapies can be identified more quickly. 5 Frost & Sullivan Big Data & Analytics Survey, 2016 All rights reserved 2017 Frost & Sullivan 7

8 Keeping up with IOT and Variable Workloads Industry: Manufacturing A manufacturing firm just brought a new, modern factory online; and its automation platform is generating a lot of Internet of Things (IOT) sensor data that the company wants to capture and utilize to improve workflow and yield. This data is needed for long-term studies, and some of it may be very active during certain seasons or to meet a surge in customer demand. IBM Cloud Object Storage Flex is perfect for this highly variable workload, which will help increase efficiency and productivity, without incurring penalties for access times and costs. Leveraging Fickle Customer Data to Derive New Insights Industry: Retail/Cross industry A retail firm continuously analyzes customer data for insights that help the company personalize its interactions with customers. Today, data is used to find trends around a customer s habits, which are typically indicative of future behavior. But now, the company is considering deriving additional value from the data, by introducing IBM Watson sentiment analysis. This solution can show the company how well, or poorly, products and experiences are being received, in near real-time. With this information, the company expects to more closely target and anticipate its customers needs, enabling it to make adjustments to offerings, and better engage the targeted audience. Because the analysis is triggered by on-going customer activity, the data access requirements are not predictable. With the IBM Flex offering, workgroups and applications will be able to access both older customer data and current trends, at any time, without financial penalty. By doing so, retailers can test customer scenarios, predict shopping and buying patterns, and improve their customers experience creating greater loyalty over time. Better Data Access in Time of Crisis Industry: Energy exploration and analytics An energy exploration firm is storing seismic data from exploration rigs from around the world. When seismic activity is severe enough to cause damage to on-shore or off-shore assets, the firm turns to similar incidents around the world to compare damage patterns, and determine the most effective remedies. This requires urgent access to archived data. By storing the data in IBM Cloud Object Storage Flex, the critical data will be immediately available and accessible, for all locations, at a reasonable cost even in times of crisis. 8 All rights reserved 2017 Frost & Sullivan

9 BOTTOM LINE: COST COMPARISONS FOR STORAGE WORKLOADS IN IBM CLOUD OBJECT STORAGE FLEX OPTION, AMAZON S3, AND AZURE BLOB STORAGE As businesses transform their IT strategies to support new digital requirements, many are rethinking their assumptions about their cloud service providers. Traditional cloud storage services (i.e., pricing and data access tiers) that may appear to work well for a few isolated workloads may not be moving the company s digital transformation strategy forward. When IT decision-makers take a closer look, they may find they can achieve greater value and momentum, at a lower cost, from IBM. In terms of cloud object storage, IBM s innovative Flex pricing means that for many evolving business situations, like those above, enterprises are likely to pay significantly less for IBM Cloud Object Storage than with other providers. In addition, IBM s unique architecture, based on patented geo-dispersal technology, provides inherent multi-regional availability, negating the need to implement (and pay for) replicated data stores in multiple regions. This can mean that IBM Cloud Object Storage users pay less than with competitors to achieve the availability levels critical to their business operations. How much can the IBM Cloud Object Storage Flex offering save companies? Consider the following comparative test for a business use case, conducted by IBM, with results reviewed by Frost & Sullivan. Sample Case Study Parameters For our purposes, let s assume that the test represents a workload mentioned earlier: that of a retail organization collecting and analyzing large amounts of customer data from various locations around the world. To ensure availability, cross-regional replication of the data is necessary. Our data store is ½ PB at the start, but will grow to 5 PB. The data is largely unstructured (e.g., social media discussions; user reviews; sentiment analysis). Ninety-five percent of stored objects are large capacity (average 275 MB), with the remaining 5% small capacity (average 3 MB). When a new promotion is launched, marketing managers, data analysts, supply chain managers, and store managers require frequent access to the data: thus, during such hot months, access patterns show that 80% of the data is read; 50% is written. As the data ages and the initial analysis is completed, the data is accessed less frequently (primarily for trending reports and predictive analytics for future promotions). In such cool months, access patterns show that 10% of the data is read, and 50% is written. Competitive Pricing Scenarios In a tiered structure the only option available with Amazon S3 and Azure Blob the retail firm places active data in a hot tier. The aged data will be placed in a cool tier and, ultimately, archived. But with IBM Cloud Object Storage Flex, all data can be placed in the Flex tier, with costs incurred based on actual (versus predicted) access, and per-gb prices subject to a budget-friendly cap. The figures below compare costs for IBM Cloud Object Storage over competitors, for storage volumes of ½ PB and 5 PB. As indicated, the tests show that IBM Cloud Object Storage delivered cost of 22 53% over Amazon S3; and 23 75% cost over Azure Blob. All rights reserved 2017 Frost & Sullivan 9

10 Figure 1: Cost Comparison for IBM Cloud Object Storage Flex and Amazon S3 Simpler Pricing for Multi-Region Availability and Durability Amazon IBM Cloud Object Storage S3 + CRR Flex Cross-Region HOT = STANDARD HOT OR COOL = FLEX COOL = INFREQUENT ACCESS Primary service price Replica service price Data replication charges IBM Cloud Object Storage Flex vs Amazon Service price (Charges based on either usage pricing or capped per GB pricing, whichever is lower) ½ Petabyte with IBM Flex 24% 53% 5 Petabytes with IBM Flex 22% 53% over Standard S3 + IA CRR in Hot Months* over IA S3 + IA CRR in Cool Months* * Comparison: IBM Cloud Object Storage Flex Cross-Region vs. S3 Hot : Standard bucket in AWS US East ( primary ) with Cross Region Replication to S3 Infrequent Access bucket in US West Oregon ( replica ) and vs. S3 Cool : S3 Infrequent Access bucket in AWS US East with Cross Region Replication to S3 Infrequent Access bucket in US West Oregon. All S3 access assumed through primary bucket. Pricing based on Amazon US list prices as of 6/12/17 and IBM Cloud Object Storage Flex pricing available starting April Price includes storage capacity, API operations, and cross-region data replication charges (S3 only). Price comparisons exclude outbound internet data transfer charges. Usage based pricing comparison based on specific workload assumptions actual customer charges will vary depending on workload, storage capacity, object sizes, data access patterns, storage tier, redundancy options, and other factors. Pricing for this comparison based on the following workload assumptions: 1) Mixed footprint of 5% "small" and 95% "large" objects (by capacity), Average object sizes: Small = 3MB, Large = 275MB. 2) Monthly access patterns: Hot : 80% read, 50% written, 5% listed. Cool : 10% read, 50% written, 5% listed. All objects assumed retained at least 30 days. IBM Cloud Object Storage: Amazon AWS S3: Source: IBM 10 All rights reserved 2017 Frost & Sullivan

11 Figure 2: Cost Comparison for IBM Cloud Object Storage Flex and Azure Blob IBM Cloud Object Storage Flex vs Azure Simpler Pricing for Multi-Region Availability and Durability ½ Petabyte with IBM Flex 5 Petabytes with IBM Flex Azure GRS Blob Storage HOT = Hot Access Tier COOL = Cool Access Tier IBM Cloud Object Storage Flex Cross-Region HOT OR COOL = FLEX 25% 23% over GRS Hot Tier in Hot Months* Primary service price Data replication charges Service price (Charges based on either usage pricing or capped per GB pricing, whichever is lower) 75% 75% over GRS Cool Tier in Cool Months* * Comparison: IBM Cloud Object Storage Flex Cross-Region vs. Azure Hot GRS in East US 2 (Primary) and vs. Azure Cool GRS in East US 2 (Primary). Pricing based on Azure US list prices as of 6/12/17 and IBM Cloud Object Storage Flex pricing available starting April Price includes storage capacity, API operations, and data replication charges (Azure only). Price comparisons exclude outbound internet data transfer charges. Usagebased pricing comparison based on specific workload assumptions actual customer charges will vary depending on workload, storage capacity, object sizes, data access patterns, storage tier, redundancy options, and other factors. Pricing for this comparison based on the following workload assumptions: 1) Mixed footprint of 5% "small" and 95% "large" objects (by capacity), Average object sizes: Small = 3MB, Large = 275MB. 2) Monthly access patterns: Hot : 80% read, 50% written, 5% listed. Cool : 10% read, 50% written, 5% listed. IBM Cloud Object Storage: Azure GRS: Source: IBM All rights reserved 2017 Frost & Sullivan 11

12 CONCLUSION In selecting a cloud object storage service, businesses need to focus first on the service that best enables them to unlock the value of stored data. When the superior service also offers 22 75% over other market leading offers, the service deserves a pivotal role in the company s technology strategy. The innovative Flex option for IBM Cloud Object Storage meets enterprise needs on both counts strategic and financial. For enterprises looking to derive more value from their stored data, but unable to predict how often that data will be accessed, Flex pricing from IBM Cloud Object Storage offers fast access to data while keeping your budget predictable. The service also offers the full range of value differentiators of IBM Cloud Object Storage, including a private cloud option (on-premises or off-premises), public cloud or hybrid cloud, plus high data resiliency without data replication and the associated costs. In the future, competitive success will often belong to the company that best utilizes data. Ensuring your company is prepared for a data-reliant future will mean selecting the right cloud object storage service one that encourages the use of data. IBM Cloud Object Storage provides a unique strategy to deliver the access and availability you need for all your stored data, at a lower and more predictable price than competitors, without sacrificing data performance. To learn more about the IBM Cloud Object Storage public cloud offering and advantages, please click here: 12 All rights reserved 2017 Frost & Sullivan

13 Silicon Valley 3211 Scott Blvd Santa Clara CA, Tel: Fax: San Antonio 7550 West Interstate 10, Suite 400 San Antonio, Texas Tel Fax London 4, Grosvenor Gardens, London SWIW ODH,U Tel 44(0) Fax 44(0) GoFrost ABOUT FROST & SULLIVAN Frost & Sullivan, the Growth Partnership Company, works in collaboration with clients to leverage visionary innovation that addresses the global challenges and related growth opportunities that will make or break today s market participants. For more than 50 years, we have been developing growth strategies for the Global 1000, emerging businesses, the public sector and the investment community. Is your organization prepared for the next profound wave of industry convergence, disruptive technologies, increasing competitive intensity, Mega Trends, breakthrough best practices, changing customer dynamics and emerging economies? Contact Us: Start the Discussion For information regarding permission, write: Frost & Sullivan 3211 Scott Blvd Santa Clara CA Auckland Dubai Moscow Silicon Valley Bahrain Frankfurt Mumbai Singapore Bangkok Iskander Malaysia/Johor Bahru Oxford Sophia Antipolis Beijing Istanbul Paris Sydney Bengaluru Jakarta Rockville Centre Taipei Buenos Aires Kolkata San Antonio Tel Aviv Cape Town Kuala Lumpur São Paulo Tokyo Chennai London Sarasota Toronto Colombo Manhattan Seoul Warsaw Delhi / NCR Miami Shanghai Washington, DC Detroit Milan Shenzhen