|By Bob Gourley||
|January 5, 2013 09:40 AM EST||
By Doug Laney
In the late 1990s, while a META Group analyst (Note: META is now part of Gartner), it was becoming evident that our clients increasingly were encumbered by their data assets. While many pundits were talking about, many clients were lamenting, and many vendors were seizing the opportunity of these fast-growing data stores, I also realized that something else was going on. Sea changes in the speed at which data was flowing mainly due to electronic commerce, along with the increasing breadth of data sources, structures and formats due to the post Y2K-ERP application boom were as or more challenging to data management teams than was the increasing quantity of data.
In an attempt to help our clients get a handle on how to recognize, and more importantly, deal with these challenges I began first speaking at industry conferences on this 3-dimensional data challenge of increasing data volume, velocity and variety. Then in late 2000 I drafted a research note published in February 2001 entitled 3-D Data Management: Controlling Data Volume, Velocity and Variety.
Fast forward to today: The “3V’s” framework for understanding and dealing with Big Data has now become ubiquitous. In fact, other research firms, major vendors and consulting firms have even posited the 3Vs (or an unmistakable variant) as their own concept. Since the original piece is no longer available in Gartner archives but is in increasing demand, I wanted to make it available here for anyone to reference and cite:
Original Research Note PDF: 3-D Data Management: Controlling Data Volume, Velocity and Variety
Date: 6 February 2001 Author: Doug Laney
3-D Data Management: Controlling Data Volume, Velocity and Variety. Current business conditions and mediums are pushing traditional data management principles to their limits, giving rise to novel and more formalized approaches.
META Trend: During 2001/02, leading enterprises will increasingly use a centralized data warehouse to define a common business vocabulary that improves internal and external collaboration. Through 2003/04, data quality and integration woes will be tempered by data profiling technologies (for generating metadata, consolidated schemas, and integration logic) and information logistics agents. By 2005/06, data, document, and knowledge management will coalesce, driven by schema-agnostic indexing strategies and portal maturity.
The effect of the e-commerce surge, a rise in merger & acquisition activity, increased collaboration, and the drive for harnessing information as a competitive catalyst is driving enterprises to higher levels of consciousness about how data is managed at its most basic level. In 2001-02, historical, integrated databases (e.g. data warehouses, operational data stores, data marts), will be leveraged not only for intended analytical purposes, but increasingly for intra-enterprise consistency and coordination. By 2003-04, these structures (including their associated metadata) will be on par with application portfolios, organization charts and procedure manuals for defining a business to its employees and affiliates.
Data records, data structures, and definitions commonly accepted throughout an enterprise reduce fiefdoms pulling against each other due to differences in the way each perceives where the enterprise has been, is presently, and is headed. Readily accessible current and historical records of transactions, affiliates (partners, employees, customers, suppliers), business processes (or rules), along with definitional and navigational metadata (see ADS Delta 896, 21st Century Metadata: Mapping the Enterprise Genome, 7 Aug 2000) enable employees to paddle in the same direction. Conversely, application-specific data stores (e.g. accounts receivable versus order status), geographic-specific data stores (e.g. North American sales vs. International sales), offer conflicting, or insular views of the enterprise, that while important for feeding transactional systems, provide no “single version of the truth,” giving rise to inconsistency in the way enterprise factions function.
While enterprises struggle to consolidate systems and collapse redundant databases to enable greater operational, analytical, and collaborative consistencies, changing economic conditions have made this job more difficult. E-commerce, in particular, has exploded data management challenges along three dimensions: volumes, velocity and variety. In 2001/02, IT organizations must compile a variety of approaches to have at their disposal for dealing with each.
E-commerce channels increase the depth and breadth of data available about a transaction (or any point of interaction). The lower cost of e-channels enables and enterprise to offer its goods or services to more individuals or trading partners, and up to 10x the quantity of data about an individual transaction may be collected—thereby increasing the overall volume of data to be managed. Furthermore, as enterprises come to see information as a tangible asset, they become reluctant to discard it.
Typically, increases in data volume are handled by purchasing additional online storage. However as data volume increases, the relative value of each data point decreases proportionately—resulting in a poor financial justification for merely incrementing online storage. Viable alternates and supplements to hanging new disk include:
- Implementing tiered storage systems (see SIS Delta 860, 19 Apr 2000) that cost effectively balance levels of data utility with data availability using a variety of media.
- Limiting data collected to that which will be leveraged by current or imminent business processes
- Limiting certain analytic structures to a percentage of statistically valid sample data.
- Profiling data sources to identify and subsequently eliminate redundancies
- Monitoring data usage to determine “cold spots” of unused data that can be eliminated or offloaded to tape (e.g. Ambeo, BEZ Systems, Teleran)
- Outsourcing data management altogether (e.g. EDS, IBM)
E-commerce has also increased point-of-interaction (POI) speed, and consequently the pace data used to support interactions and generated by interactions. As POI performance is increasingly perceived as a competitive differentiator (e.g. Web site response, inventory availability analysis, transaction execution, order tracking update, product/service delivery, etc.) so too is an organization’s ability to manage data velocity. Recognizing that data velocity management is much more than a physical bandwidth and protocol issue, enterprises are implementing architectural solutions such as:
- Operational data stores (ODSs) that periodically extract, integrate and re-organize production data for operational inquiry or tactical analysis
- Caches that provide instant access to transaction data while buffering back-end systems from additional load and performance degradation. (Unlike ODSs, caches are updated according to adaptive business rules and have schemas that mimic the back-end source.)
- Point-to-point (P2P) data routing between databases and applications (e.g. D2K, DataMirror) that circumvents high-latency hub-and-spoke models that are more appropriate for strategic analysis
- Designing architectures that balance data latency with application data requirements and decision cycles, without assuming the entire information supply chain must be near real-time.
Through 2003/04, no greater barrier to effective data management will exist than the variety of incompatible data formats, non-aligned data structures, and inconsistent data semantics. By this time, interchange and translation mechanisms will be built into most DBMSs. But until then, application portfolio sprawl (particularly when based on a “strategy” of autonomous software implementations due to e-commerce solution immaturity), increased partnerships, and M&A activity intensifies data variety challenges. Attempts to resolve data variety issues must be approached as an ongoing endeavor encompassing the following techniques:
- Data profiling (e.g. Data Mentors, Metagenix) to discover hidden relationships and resolve inconsistencies across multiple data sources (see ADS898)
- XML-based data format “universal translators” that import data into standard XML documents for export into another data format (e.g. infoShark, XML Solutions)
- Enterprise application integration (EAI) predefined adapters (e.g. NEON, Tibco, Mercator) for acquiring and delivering data between known applications via message queues, or EAI development kits for building custom adapters.
- Data access middleware (e.g. Information Builders’ EDA/SQL, SAS Access, OLE DB, ODBC) for direct connectivity between applications and databases
- Distributed query management (DQM) software (e.g. Enth, InfoRay, Metagon) that adds a data routing and integration intelligence layer above “dumb” data access middleware
- Metadata management solutions (i.e. repositories and schema standards) to capture and make available definitional metadata that can help provide contextual consistency to enterprise data
- Advanced indexing techniques for relating (if not physically integrating) data of various incompatible types (e.g. multimedia, documents, structured data, business rules).
As with any sufficiently fashionable technology, users should expect the data management market place ebb-and-flow to yield solutions that consolidate multiple techniques and solutions that are increasingly application/environment specific. (See Figure 1 – Data Management Solutions) In selecting a technique or technology, enterprises should first perform an information audit assessing the status of their information supply chain to identify and prioritize particular data management issues.
Business Impact: Attention to data management, particularly in a climate of e-commerce and greater need for collaboration, can enable enterprises to achieve greater returns on their information assets.
Bottom Line: In 2001/02, IT organizations must look beyond traditional direct brute force physical approaches to data management. Through 2003/04, practices for resolving e-commerce accelerated data volume, velocity and variety issues will become more formalized and diverse. Increasingly, these techniques involve trade-offs and architectural solutions that involve and impact application portfolios and business strategy decisions.
Over the past decade, Gartner analysts including Regina Casonato, Anne Lapkin, Mark A. Beyer, Yvonne Genovese and Ted Friedman have continued to expand our research on this topic, identifying and refining other “big data” concepts. In September 2011 they published the tremendous research note Information Management in the 21st Century. And in 2012, Mark Beyer and I developed and published Gartner’s updated definition of Big Data to reflect its value proposition and requirements for “new innovative forms of processing.” (See The Importance of ‘Big Data’: A Definition)
Doug Laney is a research vice president for Gartner Research, where he covers business analytics solutions and projects, information management, and data-governance-related issues. He is considered a pioneer in the field of data warehousing and created the first commercial project methodology for business intelligence/data warehouse projects. Mr. Laney is also originated the discipline of information economics (infonomics).
Follow Doug on Twitter: @Doug_Laney
20th Cloud Expo, taking place June 6-8, 2017, at the Javits Center in New York City, NY, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy.
Dec. 10, 2016 11:30 AM EST Reads: 2,019
Infrastructure is widely available, but who’s managing inbound/outbound traffic? Data is created, stored, and managed online – who is protecting it and how? In his session at 19th Cloud Expo, Jaeson Yoo, SVP of Business Development at Penta Security Systems Inc., discussed how to keep any and all infrastructure clean, safe, and efficient by monitoring and filtering all malicious HTTP/HTTPS traffic at the OSI Layer 7. Stop attacks and web intruders before they can enter your network.
Dec. 10, 2016 11:00 AM EST Reads: 484
The many IoT deployments around the world are busy integrating smart devices and sensors into their enterprise IT infrastructures. Yet all of this technology – and there are an amazing number of choices – is of no use without the software to gather, communicate, and analyze the new data flows. Without software, there is no IT. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, Dave McCarthy, Director of Products at Bsquare Corporation; Alan Williamson, Principal...
Dec. 10, 2016 11:00 AM EST Reads: 689
In his session at Cloud Expo, Robert Cohen, an economist and senior fellow at the Economic Strategy Institute, provideed economic scenarios that describe how the rapid adoption of software-defined everything including cloud services, SDDC and open networking will change GDP, industry growth, productivity and jobs. This session also included a drill down for several industries such as finance, social media, cloud service providers and pharmaceuticals.
Dec. 10, 2016 11:00 AM EST Reads: 657
Extracting business value from Internet of Things (IoT) data doesn’t happen overnight. There are several requirements that must be satisfied, including IoT device enablement, data analysis, real-time detection of complex events and automated orchestration of actions. Unfortunately, too many companies fall short in achieving their business goals by implementing incomplete solutions or not focusing on tangible use cases. In his general session at @ThingsExpo, Dave McCarthy, Director of Products...
Dec. 10, 2016 11:00 AM EST Reads: 1,006
Internet of @ThingsExpo has announced today that Chris Matthieu has been named tech chair of Internet of @ThingsExpo 2017 New York The 7th Internet of @ThingsExpo will take place on June 6-8, 2017, at the Javits Center in New York City, New York. Chris Matthieu is the co-founder and CTO of Octoblu, a revolutionary real-time IoT platform recently acquired by Citrix. Octoblu connects things, systems, people and clouds to a global mesh network allowing users to automate and control design flo...
Dec. 10, 2016 10:30 AM EST Reads: 905
Unsecured IoT devices were used to launch crippling DDOS attacks in October 2016, targeting services such as Twitter, Spotify, and GitHub. Subsequent testimony to Congress about potential attacks on office buildings, schools, and hospitals raised the possibility for the IoT to harm and even kill people. What should be done? Does the government need to intervene? This panel at @ThingExpo New York brings together leading IoT and security experts to discuss this very serious topic.
Dec. 10, 2016 10:15 AM EST Reads: 630
Businesses and business units of all sizes can benefit from cloud computing, but many don't want the cost, performance and security concerns of public cloud nor the complexity of building their own private clouds. Today, some cloud vendors are using artificial intelligence (AI) to simplify cloud deployment and management. In his session at 20th Cloud Expo, Ajay Gulati, Co-founder and CEO of ZeroStack, will discuss how AI can simplify cloud operations. He will cover the following topics: why clou...
Dec. 10, 2016 10:00 AM EST Reads: 1,081
In this strange new world where more and more power is drawn from business technology, companies are effectively straddling two paths on the road to innovation and transformation into digital enterprises. The first path is the heritage trail – with “legacy” technology forming the background. Here, extant technologies are transformed by core IT teams to provide more API-driven approaches. Legacy systems can restrict companies that are transitioning into digital enterprises. To truly become a lead...
Dec. 10, 2016 09:45 AM EST Reads: 631
Internet-of-Things discussions can end up either going down the consumer gadget rabbit hole or focused on the sort of data logging that industrial manufacturers have been doing forever. However, in fact, companies today are already using IoT data both to optimize their operational technology and to improve the experience of customer interactions in novel ways. In his session at @ThingsExpo, Gordon Haff, Red Hat Technology Evangelist, will share examples from a wide range of industries – includin...
Dec. 10, 2016 09:00 AM EST Reads: 1,783
"We analyze the video streaming experience. We are gathering the user behavior in real time from the user devices and we analyze how users experience the video streaming," explained Eric Kim, Founder and CEO at Streamlyzer, in this SYS-CON.tv interview at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 10, 2016 07:30 AM EST Reads: 786
Enterprise IT has been in the era of Hybrid Cloud for some time now. But it seems most conversations about Hybrid are focused on integrating AWS, Microsoft Azure, or Google ECM into existing on-premises systems. Where is all the Private Cloud? What do technology providers need to do to make their offerings more compelling? How should enterprise IT executives and buyers define their focus, needs, and roadmap, and communicate that clearly to the providers?
Dec. 10, 2016 06:00 AM EST Reads: 718
"We are a leader in the market space called network visibility solutions - it enables monitoring tools and Big Data analysis to access the data and be able to see the performance," explained Shay Morag, VP of Sales and Marketing at Niagara Networks, in this SYS-CON.tv interview at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 10, 2016 04:30 AM EST Reads: 572
According to Forrester Research, every business will become either a digital predator or digital prey by 2020. To avoid demise, organizations must rapidly create new sources of value in their end-to-end customer experiences. True digital predators also must break down information and process silos and extend digital transformation initiatives to empower employees with the digital resources needed to win, serve, and retain customers.
Dec. 10, 2016 04:15 AM EST Reads: 1,394
Amazon has gradually rolled out parts of its IoT offerings in the last year, but these are just the tip of the iceberg. In addition to optimizing their back-end AWS offerings, Amazon is laying the ground work to be a major force in IoT – especially in the connected home and office. Amazon is extending its reach by building on its dominant Cloud IoT platform, its Dash Button strategy, recently announced Replenishment Services, the Echo/Alexa voice recognition control platform, the 6-7 strategic...
Dec. 10, 2016 04:15 AM EST Reads: 590
Organizations planning enterprise data center consolidation and modernization projects are faced with a challenging, costly reality. Requirements to deploy modern, cloud-native applications simultaneously with traditional client/server applications are almost impossible to achieve with hardware-centric enterprise infrastructure. Compute and network infrastructure are fast moving down a software-defined path, but storage has been a laggard. Until now.
Dec. 10, 2016 04:00 AM EST Reads: 5,556
We're entering the post-smartphone era, where wearable gadgets from watches and fitness bands to glasses and health aids will power the next technological revolution. With mass adoption of wearable devices comes a new data ecosystem that must be protected. Wearables open new pathways that facilitate the tracking, sharing and storing of consumers’ personal health, location and daily activity data. Consumers have some idea of the data these devices capture, but most don’t realize how revealing and...
Dec. 10, 2016 04:00 AM EST Reads: 5,322
IoT solutions exploit operational data generated by Internet-connected smart “things” for the purpose of gaining operational insight and producing “better outcomes” (for example, create new business models, eliminate unscheduled maintenance, etc.). The explosive proliferation of IoT solutions will result in an exponential growth in the volume of IoT data, precipitating significant Information Governance issues: who owns the IoT data, what are the rights/duties of IoT solutions adopters towards t...
Dec. 10, 2016 03:15 AM EST Reads: 515
Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance – how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders – from customers to the board – will be able to understand and comprehe...
Dec. 10, 2016 02:15 AM EST Reads: 811
Between 2005 and 2020, data volumes will grow by a factor of 300 – enough data to stack CDs from the earth to the moon 162 times. This has come to be known as the ‘big data’ phenomenon. Unfortunately, traditional approaches to handling, storing and analyzing data aren’t adequate at this scale: they’re too costly, slow and physically cumbersome to keep up. Fortunately, in response a new breed of technology has emerged that is cheaper, faster and more scalable. Yet, in meeting these new needs they...
Dec. 10, 2016 02:00 AM EST Reads: 1,998