Tuesday, December 16, 2014

Gartner Magic Quadrant for Data Quality Tools : 2014

Informatica, IBM, Trillium Software, SAS & SAP are in the leaders quadrant for “Gartner Magic Quadrant for Data Quality Tools : 2014”

Market Definition/Description
Data quality assurance is a discipline that focuses on ensuring data is fit for use in business processes. These processes range from those used in core operations to those required by analytics and for decision making, regulatory compliance, and engagement and interaction with external entities.
As a discipline, data quality assurance covers much more than technology. It also includes roles and organizational structures; processes for monitoring, measuring, reporting and remediating data quality issues; and links to broader information governance activities via data-quality-specific policies.

Given the scale and complexity of the data landscape, across organizations of all sizes and in all industries, tools to help automate key elements of this discipline continue to attract more interest and to grow in value. As such, the data quality tools market continues to show substantial growth, while also exhibiting innovation and change.

This market includes vendors that offer stand-alone software products to address the core functional requirements of the discipline, which are:
Data profiling and data quality measurement: The analysis of data to capture statistics (metadata) that provide insight into the quality of data and help to identify data quality issues.
Parsing and standardization: The decomposition of text fields into component parts and the formatting of values into consistent layouts, based on industry standards, local standards (for example, postal authority standards for address data), user-defined business rules, and knowledge bases of values and patterns.
Generalized "cleansing": The modification of data values to meet domain restrictions, integrity constraints or other business rules that define when the quality of data is sufficient for an organization.
Matching: The identifying, linking or merging of related entries within or across sets of data.
Monitoring: The deployment of controls to ensure that data continues to conform to business rules that define data quality for an organization.
Issue resolution and workflow: The identification, quarantining, escalation and resolution of data quality issues through processes and interfaces that enable collaboration with key roles, such as data steward.
Enrichment: The enhancement of the value of internally held data by appending related attributes from external sources (for example, consumer demographic attributes and geographic descriptors).

Monday, December 15, 2014

Gartner Magic Quadrant for Data Masking Technology - 2014

Gartner estimated that the overall SDM (static data masking) revenue of vendors in this Magic Quadrant will be approximately $300 million in 2014 — up from approximately $190 million in 2013 — thus making revenue growth close to 60% over the period of one year. More than 75% of this 2014 revenue has been earned by the three Leaders, while less than 25% has been earned by the other 11 vendors. This disproportion is worrisome to smaller IT vendors because it demonstrates their lack of ability to reach their target audiences, even though some of them have strong technical features with which to challenge Leaders.

IBM, Informatica & Oracle are leading the pack of “Gartner Magic Quadrant for Data Masking Technology – 2014”.

Market Definition/Description
Data masking (DM) is a technology aimed at preventing the abuse of sensitive data by giving users fictitious (yet realistic) data instead of real sensitive data. It aims to deter the misuse of data at rest, typically in nonproduction databases (static data masking [SDM]), and data in transit, typically in production databases (dynamic data masking [DDM]).

SDM for relational databases remains the most demanded technology, and, in this research, we highly value vendors' ability to execute in the SDM space (that is, to demonstrate maturity, quality and scalability of SDM technology, as well as the high revenue from and broad adoption of it). From a visionary's viewpoint, we highly value vendors' ability to offer DDM, the masking of the big data platform and suites with multiple data security technologies.

Tuesday, November 11, 2014

Gartner identifies top ten strategic technology trends for 2015

Gartner defines a strategic technology trend as one with the potential for significant impact on the organization in the next three years. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization's long-term plans, programs and initiatives.

Computing Everywhere
As mobile devices continue to proliferate, Gartner predicts an increased emphasis on serving the needs of the mobile user in diverse contexts and environments, as opposed to focusing on devices alone.

The Internet of Things
The combination of data streams and services created by digitizing everything creates four basic usage models — Manage, Monetize, Operate and Extend. These four basic models can be applied to any of the four "Internets." Enterprises should not limit themselves to thinking that only the Internet of Things (IoT) (assets and machines) has the potential to leverage these four models. For example, the pay-per-use model can be applied to assets (such as industrial equipment), services (such as pay-as-you-drive insurance), people (such as movers), places (such as parking spots) and systems (such as cloud services). Enterprises from all industries can leverage these four models.

3D Printing
Worldwide shipments of 3D printers are expected to grow 98 percent in 2015, followed by a doubling of unit shipments in 2016. 3D printing will reach a tipping point over the next three years as the market for relatively low-cost 3D printing devices continues to grow rapidly and industrial use expands significantly. New industrial, biomedical and consumer applications will continue to demonstrate that 3D printing is a real, viable and cost-effective means to reduce costs through improved designs, streamlined prototyping and short-run manufacturing.

Advanced, Pervasive and Invisible Analytics
Analytics will take center stage as the volume of data generated by embedded systems increases and vast pools of structured and unstructured data inside and outside the enterprise are analyzed. "Every app now needs to be an analytic app," said Mr. Cearley. "Organizations need to manage how best to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time. Analytics will become deeply, but invisibly embedded everywhere." Big data remains an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and big data second — the value is in the answers, not the data.

Context-Rich Systems
Ubiquitous embedded intelligence combined with pervasive analytics will drive the development of systems that are alert to their surroundings and able to respond appropriately. Context-aware security is an early application of this new capability, but others will emerge. By understanding the context of a user request, applications can not only adjust their security response but also adjust how information is delivered to the user, greatly simplifying an increasingly complex computing world.

Smart Machines
Deep analytics applied to an understanding of context provide the preconditions for a world of smart machines. This foundation combines with advanced algorithms that allow systems to understand their environment, learn for themselves, and act autonomously. Prototype autonomous vehicles, advanced robots, virtual personal assistants and smart advisors already exist and will evolve rapidly, ushering in a new age of machine helpers. The smart machine era will be the most disruptive in the history of IT.

Cloud/Client Computing
The convergence of cloud and mobile computing will continue to promote the growth of centrally coordinated applications that can be delivered to any device. "Cloud is the new style of elastically scalable, self-service computing, and both internal applications and external applications will be built on this new style," said Mr. Cearley. "While network and bandwidth costs may continue to favor apps that use the intelligence and storage of the client device effectively, coordination and management will be based in the cloud."

Software-Defined Applications and Infrastructure
Agile programming of everything from applications to basic infrastructure is essential to enable organizations to deliver the flexibility required to make the digital business work. Software-defined networking, storage, data centers and security are maturing. Cloud services are software-configurable through API calls, and applications, too, increasingly have rich APIs to access their function and content programmatically. To deal with the rapidly changing demands of digital business and scale systems up — or down — rapidly, computing has to move away from static to dynamic models. Rules, models and code that can dynamically assemble and configure all of the elements needed from the network through the application are needed.

Web-Scale IT Web-scale
IT is a pattern of global-class computing that delivers the capabilities of large cloud service providers within an enterprise IT setting. More organizations will begin thinking, acting and building applications and infrastructure like Web giants such as Amazon, Google and Facebook. Web-scale IT does not happen immediately, but will evolve over time as commercial hardware platforms embrace the new models and cloud-optimized and software-defined approaches reach mainstream. The first step toward the Web-scale IT future for many organizations should be DevOps — bringing development and operations together in a coordinated way to drive rapid, continuous incremental development of applications and services.

Risk-Based Security and Self-Protection
All roads to the digital future lead through security. However, in a digital business world, security cannot be a roadblock that stops all progress. Organizations will increasingly recognize that it is not possible to provide a 100 percent secured environment. Once organizations acknowledge that, they can begin to apply more-sophisticated risk assessment and mitigation tools. On the technical side, recognition that perimeter defense is inadequate and applications need to take a more active role in security gives rise to a new multifaceted approach. Security-aware application design, dynamic and static application security testing, and runtime application self-protection combined with active context-aware and adaptive access controls are all needed in today's dangerous digital world. This will lead to new models of building security directly into applications. Perimeters and firewalls are no longer enough; every app needs to be self-aware and self-protecting.

Read more at: http://www.informationweek.in/informationweek/press-releases/298228/gartner-identifies-strategic-technology-trends-2015?utm_source=referrence_article 

Tuesday, November 4, 2014

2014 Gartner Magic Quadrant for Master Data Management of Customer Data Solutions

Businesses of all sizes and in many industries are struggling to maintain a consistent, shareable and accurate single version of customer data across their organizations — a requirement that is growing in importance. With the increasing focus on the digitalization of enterprises, management of their key master data is also becoming more important. The ability to achieve and maintain a single, semantically consistent version of customer master data is crucial for customer-centric organizations.

IBM, Informatica, Oracle & Tibco are in the Leaders Quadrant of "Gartner Magic Quadrant for Master Data Management of Customer Data Solutions 2014" considering following criteria by Gartner.
·         Data-modeling capabilities
·         Information quality and semantic capabilities
·         Business services, integration and synchronization
·         Workflow and BPM capabilities
·         Performance, scalability, security and availability capabilities
·         Stewardship support and services
·         Technology and architectural considerations

·         Information governance support 

Market Definition/Description
Master data management (MDM) of customer data solutions are software products that:
ü  Support the global identification, linking and synchronization of customer information across heterogeneous data sources through semantic reconciliation of master data
ü  Create and manage a central, persisted system of record or index of record for master data
ü  Enable delivery of a single customer view to all stakeholders, in support of various business benefits
ü  Support ongoing master data stewardship and governance requirements through workflow-based monitoring and corrective-action techniques

Tuesday, October 28, 2014

Gartner Magic Quadrant for Operational Database Management Systems 2014

The operational DBMS market continues to grow, with innovative products and features being delivered by both new and traditional vendors. Information management leaders will be particularly interested by the changes in the Leaders quadrant.

Gartner's Strategic Planning Assumptions
By 2017, the "NoSQL" label will cease to distinguish DBMSs, which will reduce its value and result in it falling out of use.
By 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single platform.

IBM, Oracle, Microsoft, SAP, InterSystems, EnterpriseDB (PostgreSQL), MarkLogic & MariaDB are in the Leaders Quadrant of "Magic Quadrant for Operational Database Management Systems 2014"

Market Definition/Description
The operational database management system (DBMS) market is defined by relational and nonrelational database management products that are suitable for a broad range of enterprise-level transactional applications. These include purchased business applications such as enterprise resource planning (ERP), customer relationship management and customized transactional systems built by an organization's development team. In addition, Gartner include DBMS products that also support interaction data and observation data as new transaction types. These products are also used both for purchased business applications, such as ERP, catalog management and security event management, and for customized systems.

Operational DBMSs must include functionality to support backup and recovery, and have some form of transaction durability — although the atomicity, consistency, isolation and durability (ACID) model is not a requirement. For open-source DBMSs, maintenance and support must be available from a vendor that owns, or has substantial control over, the source code, and must be offered with a full General Public License (GPL) or an alternative.

For this Magic Quadrant, Gartner define operational DBMSs as systems that support multiple structures and data types, such as XML, text, JavaScript Object Notation (JSON), audio, image and video content. They must include mechanisms to isolate workload resources and control various parameters of end-user access within managed instances of data . Emerging technologies, such as cloud-only DBMSs, are not included; nor are highly specialized engines such as graph-only or object databases, which may perform some transactions for small subsets of operational use cases. Products that "add a layer" to and require or embed a complete or near-complete implementation of another commercially marketed product, such as Oracle MySQL, are not included. Finally, "streaming" engines, whose use cases are dominated by immediate event processing, and which are rarely, if ever, used for subsequent management of the data involved, are also excluded.

Friday, October 17, 2014

Gartner Magic Quadrant for Web Content Management: 2014

Web content management is no longer simply a tool for creating Web pages — it's now vital software for increasing the effectiveness of digital strategies. IT leaders responsible for WCM should consider the software's functions in the broader context in which they will deliver their full value.

IBM, Adobe, HP, Oracle, Acquia & Sitecore are in the leader’s quadrant in ‘Gartner Magic Quadrant for Web Content Management: 2014’ .

Gartner defines Web content management (WCM) as the process of controlling content to be consumed over one or more digital channels through the use of management software based on a core repository. These may be commercial products, open-source or hosted service offerings. Product functions go beyond simply publishing Web pages, to include:
  • Content creation functions, such as templating, workflow and change management.
  • WCM repositories that contain content or metadata about the content.
  • Library services, such as check-in/check-out, version control and security.
  • Content deployment functions that deliver prepackaged or on-demand content to Web servers.
  • A high degree of interoperability with adjacent technologies, such as CRM, multichannel campaign management (MCCM), marketing resource management, digital asset management (DAM) and Web analytics.
  • Real-time adaptation to visitor interaction through a delivery engine, an enhanced framework for delivery applications or similar. Some products also integrate well with delivery tiers such as e-commerce, social media and portal software.

Thursday, September 11, 2014

The Forrester Wave™: Web Analytics, Q2 2014

Adobe, AT Internet, IBM, And Webtrends Are Leaders In Enterprise Web Analytics

For more refer: http://webtrends.com/files/report/Report-Forrester_Wave_Web_Analytics.pdf 

Wednesday, August 13, 2014

Gartner Hype Cycle 2014 and its 2000 digital business technologies

 New Hype Cycles this year include Digital Workplace, Connected Homes, Enterprise Mobile Security, 3D Printing and Smart Machines.

Gartner’s road map to digital business is made up of 6 models –  analog, web, e-business, digital marketing, digital business, autonomous – with the focus this year on the last three.
  • Digital Marketing tech includes: Software-Defined Anything; Volumetric and Holographic Displays; Neurobusiness; Data Science; Prescriptive Analytics; Complex Event Processing; Big Data; In-Memory DBMS; Content Analytics; Hybrid Cloud Computing; Gamification; Augmented Reality; Cloud Computing; NFC; Virtual Reality; Gesture Control; In-Memory Analytics; Activity Streams; Speech Recognition.
  • Digital Business tech includes: Bioacoustic Sensing; Digital Security; Smart Workspace; Connected Home; 3D Bioprinting Systems; Affective Computing; Speech-to-Speech Translation; Internet of Things; Cryptocurrencies; Wearable User Interfaces; Consumer 3D Printing; Machine-to-Machine Communication Services; Mobile Health Monitoring; Enterprise 3D Printing; 3D Scanners; Consumer Telematics.
  • Autonomous stage tech include:   Virtual Personal Assistants; Human Augmentation; Brain-Computer Interface; Quantum Computing; Smart Robots; Biochips; Smart Advisors; Autonomous Vehicles; Natural-Language Question Answering.
From: http://diginomica.com/2014/08/12/gartnerhypecycle/#.U-tgvfmSwaA 

Wednesday, July 30, 2014

Gartner Magic Quadrant for Data Integration Tools : 2014

The demand for data integration tools emphasizes broad applicable use, a well-integrated portfolio and interoperability with information and application infrastructures. Flexible deployment and scalability are still expected, while interest in business-facing and platform-as-a-service models grows.

Informatica, IBM (InfoSphere Suite), SAP (SAP DS ..), Oracle (ODI, OWB ..), SAS (SAS DMP..) are in the leader's quadrant. Gartner has consider broadly following criteria as given below:

  • Connectivity/adapter capabilities (data source and target support)
  • Data delivery capabilities
  • Data transformation capabilities
  • Metadata and data modeling capabilities
  • Design and development environment capabilities
  • Data governance support capabilities (via interoperation with data quality, profiling and mining capabilities)
  • Deployment options and runtime platform capabilities
  • Operations and administration capabilities
  • Architecture and integration capabilities
  • Service enablement capabilities

For more please refer: http://www.informatica.com/us/data-integration-magic-quadrant/?ref=wwwlnkpr#fbid=oP2vqjqI1WB 

Monday, July 28, 2014

Magic Quadrant for Structured Data Archiving and Application Retirement

Structured data archiving describes the ability to index, migrate and protect application data in secondary databases or flat files typically located on lower-cost storage for policy-based retention. It makes data available in context and protects it in the event of litigation or an audit. 

IBM, Informatica, HP, Solix Technologies are in the leader's quadrant.

Refer : http://www.informatica.com/us/data-archiving-magic-quadrant/?ref=wwwbnrhp#fbid=oP2vqjqI1WB

Thursday, July 17, 2014

Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014

Software AG, IBM, Informatica, SAP & Tibco are the leader in 'Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014'.

Business won’t wait. That is truer today than ever before because of the white-water flow of data from innumerable real-time data sources. Market data, clickstream, mobile devices, sensors, and even good old fashioned transactions may contain valuable, but perishable insights. Perishable because the insights are only valuable if you can detect and act on them right now. That’s where streaming analytics platforms can help. Forrester defines streaming analytics platform as:

Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple disparate live data sources and in any data format to identify simple and complex patterns to visualize business in real-time, detect urgent situations, and automate immediate actions.

For more please refer: https://info.softwareag.com/apama-leader-forrester-wave-big-data-streaming-analytics-solution.html 

Monday, July 7, 2014

The Forrester Wave™: Agile Business Intelligence Platforms, Q3 2014

Forrester’s research uncovered a market in which SAS, Tibco Software, Information Builders, Microsoft, MicroStrategy, SAP, Qlik, and Tableau Software lead the pack. Actuate, Birst, Panorama Software, Pentaho, GoodData, Tibco Jaspersoft, and IBM offer competitive options. Oracle lags behind.

For more refer: http://www.forrester.com/The+Forrester+Wave+Agile+Business+Intelligence+Platforms+Q3+2014/fulltext/-/E-RES115485

Thursday, June 26, 2014

The Forrester Wave™: Data Governance Tools, Q2 2014

Data-driven opportunities for competitive advantage abound. As a consequence, the importance of data governance — and the need for tooling to facilitate data governance —is rising. Data governance has shifted from a technology management endeavor to a business imperative. IBM, Informatica and Collibra are in leadership position for Data Governance tool in ‘The Forrester Wave™: Data Governance Tools, Q2 2014’ report.

For more please refer : http://www.informatica.com/us/assets/gated/en_forrester-wave-data-governance_analyst-report_2663.pdf

Monday, May 26, 2014

The Forrester Wave™: Product Information Management (PIM), Q2 2014

Hybris (An SAP Company), IBM, Informatica, Riversand, And Stibo Systems Lead The Pack

For more please refer: 

Tuesday, May 20, 2014

Magic Quadrant for Advanced Analytics Platforms : 2014

SAS, IBM, RapidMiner & Knime are in the leaders quadrant of "Magic Quadrant for Advanced Analytics Platforms - 2014".

For more please refer: http://www.gartner.com/technology/reprints.do?id=1-1QXWE6S&ct=140219&st=sb.

Thursday, March 13, 2014

Magic Quadrant for Data Warehouse Database Management Systems 2014

Teradata, Oracle, IBM, Microsoft & SAP are in the leader quadrant. This time in 2014, this Magic Quadrant introduces non-relational data management systems for the first time. No specific rating advantage is given regarding the type of data store used (for example, DBMS, Hadoop Distributed File System [HDFS]; relational, key-value, document; row, column and so on).

Please refer for more: http://www.gartner.com/technology/reprints.do?id=1-1RP452A&ct=140310&st=sb 

Monday, February 24, 2014

Magic Quadrant for Business Intelligence and Analytics Platforms : 2014

Magic Quadrant for Business Intelligence and Analytics Platforms for 2014 is out. 

Tableau, Qlikview, Microsoft, IBM, SAP, SAS, Tibco, Oracle, Microstrategy & Information Builder are in the leader's quadrant. 

For more please refer : http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb

Sunday, February 9, 2014

The Forrester Wave™: Master Data Management Solutions, Q1 2014

IBM’s strength is coordinating for the entire data platform, Informatica’s strength is universal MDM, and SAP’s strength is putting the business in control. Talend in the contenders giving high time to Oracle. For more, refer attached "The Forrester Wave™: Master Data Management Solutions, Q1 2014".