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    <title>Bloor - Latest research</title>
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    <description>The latest  research from the Bloor website.</description>
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		<title>Data Governance 2017</title>
		<link>http://www.bloorresearch.com/research/market-update/data-governance-2017/</link>
		<pubDate>Thu, 07 Dec 2017 00:00:00 +0000</pubDate>
		<category>Market Update</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>This Market Update compares the capabilities of various data governance vendors. We have observed that the data governance space is rapidly advancing beyond products that only provide data quality. Accordingly, we have only included vendors that offer additional governance capabilities, such as data stewardship and policy management, and have evaluated them in large part on this basis. Other areas of consideration include usability, business orientation, and data cataloguing in support of data governance.</p>      		 ]]></description>
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		<title>Collibra Data Governance Center</title>
		<link>http://www.bloorresearch.com/research/indetail/collibra-data-governance-center/</link>
		<pubDate>Wed, 29 Nov 2017 09:00:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>In this paper, we discuss Collibra Data Governance Center and its data governance capabilities. Data Governance Center is a data governance platform and suite of applications that emphasises policy management. We focus our evaluation on its capabilities in this area, as well as in data privacy, data quality monitoring and data cataloguing. The latter capability is provided by Collibra Catalog, an optional addition to the suite.</p>      		 ]]></description>
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    	<item>
		<title>Policy&#45;based Data Governance</title>
		<link>http://www.bloorresearch.com/research/incomparison/policy-based-data-governance/</link>
		<pubDate>Mon, 06 Nov 2017 09:00:00 +0000</pubDate>
		<category>InComparison</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2348</guid>
		<description><![CDATA[
      	  		<p>This paper compares the offerings provided by DATUM, Collibra and Informatica with respect to policy-driven data governance. That is, the comparison excludes data cleansing and associated technologies (data profiling, matching and so forth) as well as master data management. Conversely, it includes consideration of data catalogues, policy management, data stewardship and so on.</p>      		 ]]></description>
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		<title>DATUM Information Value Management &#45; a business value approach to digital transformation</title>
		<link>http://www.bloorresearch.com/research/white-paper/datum-information-value-management-a-business-value-approach-to-digital-transformation/</link>
		<pubDate>Mon, 06 Nov 2017 09:00:00 +0000</pubDate>
		<category>White Paper</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>In this paper, we discuss why we believe that understanding the business value of data is a pre-requisite for a successful digital transformation, and why it is fundamental to policy-driven data governance.</p>
<p>We then go on to discuss DATUM Information Value Management. The basic idea behind this is that if data is a strategic corporate asset then information management needs to be regarded as strategic also. That in turn means that it needs to be business-driven and motivated and led by business priorities and goals. It is important to have a reusable framework for governing your data that can be re-deployed across multiple business initiatives on an ongoing basis.</p>      		 ]]></description>
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    	<item>
		<title>Single Customer View</title>
		<link>http://www.bloorresearch.com/research/white-paper/single-customer-view/</link>
		<pubDate>Mon, 23 Oct 2017 09:04:00 +0000</pubDate>
		<category>White Paper</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2338</guid>
		<description><![CDATA[
      	  		<p>The concept of a single customer view (SCV) has been around for a long time, but it has become even more relevant with advent of the EU's General Data Protection Regulation (GDPR). This paper discusses different approaches to constructing an SCV: from relying on data quality and associated processes to full-scale master data management solutions.</p>      		 ]]></description>
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    	<item>
		<title>Data Lake Management</title>
		<link>http://www.bloorresearch.com/research/market-update/data-lake-management-p1/</link>
		<pubDate>Mon, 23 Oct 2017 08:59:00 +0000</pubDate>
		<category>Market Update</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>Anecdotal evidence suggests that many companies are not deriving the benefits they expected from data lake projects. The main reasons for this is that data lakes are not well managed, and it is difficult for users to find or understand the data that is within these data lakes. This paper discusses the requirements for a well-managed and governed and data lake, and assesses the various tools and products that are available on the market to accomplish this.</p>      		 ]]></description>
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    	<item>
		<title>Data Lake Management</title>
		<link>http://www.bloorresearch.com/research/spotlight/data-lake-management-spotlight/</link>
		<pubDate>Thu, 19 Oct 2017 11:20:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard, Daniel Howard)</author>
		<dc:creator>Philip Howard, Daniel Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>Part of the reason data lakes have become popular is that setting up a basic data lake is inexpensive and easy: all you really need is some spare hardware and Hadoop and you're off to the races. Unfortunately, without additional software, such lakes are likely to fail when used for anything substantial due to lack of effective processes. This is exacerbated by the open source nature of the data lake community: many software offerings available are open source, and therefore cheap to try out. However, in part because of the proliferation of open source software on the data lake, there are no pre-packaged, one-size-fits-all solutions available. This makes it difficult to build a truly effective data lake, as a suite of mostly open source solutions must be assembled manually to address a variety of issues. This paper discusses these issues and how they might be addressed. A companion paper to this - a Market Update on Data Lake Management - discusses the solutions provided by a range of vendors, in order to prevent your lake turning into a swamp.</p>      		 ]]></description>
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    	<item>
		<title>MiniMag Issue #5 &#45; September 2017 &#45; Trust</title>
		<link>http://www.bloorresearch.com/research/minimag/minimag-issue-5-september-2017-trust/</link>
		<pubDate>Tue, 26 Sep 2017 08:00:00 +0000</pubDate>
		<category>MiniMag</category>
						<author>admin@bloor.eu (David Norfolk)</author>
		<dc:creator>David Norfolk</dc:creator>
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		<description><![CDATA[
      	  		<p>Welcome to the September 2017 issue of the Bloor MiniMag.</p>
<p>The theme for this issue is TRUST, an essential underpinning for the Mutable Enterprise. At the very highest level, TRUST is about all the stakeholders in an organisation being able to sleep at night. This means, for example, the CEO being confident that his/her vision is being executed in day-to-day operations; technicians being confident that their changes will go through without crashing production; auditors being confident that the figures in their regulatory returns are correct; customers being confident that they have bought what they thought they bought and that payment will go through once and once only; and more.</p>      		 ]]></description>
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		<title>Exploding the myths of SAP HANA</title>
		<link>http://www.bloorresearch.com/research/white-paper/exploding-the-myths-of-sap-hana/</link>
		<pubDate>Mon, 04 Sep 2017 16:05:00 +0000</pubDate>
		<category>White Paper</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2339</guid>
		<description><![CDATA[
      	  		<p>If you are a long-time SAP application user then SAP would you like you to migrate to SAP HANA. However, this is not a simple decision: it is an expensive option, and it is disruptive from a technical point of view. In addition, SAP HANA is a brand as much as a product, and it means different things in different contexts. The alternative, for SAP users, is to continue with the status quo, at least for the time being. In practice, this means sticking with SAP Business Suite applications based on third-party database products. In this paper, we discuss these and associated issues.</p>      		 ]]></description>
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    	<item>
		<title>Informatica Data Governance</title>
		<link>http://www.bloorresearch.com/research/indetail/informatica-data-governance/</link>
		<pubDate>Mon, 04 Sep 2017 08:00:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>In this paper, we discuss Informatica's Intelligent Data Platform and, in particular, its data governance capabilities. Our evaluation is centred around three products - Axon, Enterprise Information Catalog, and Secure@Source - that form the bulk of the platform's data governance offering. Each of these has a specific capability: Axon provides data quality monitoring, and consequently organisational understanding; Enterprise Information Catalog is a data catalogue; and Secure@Source focuses on data security and privacy. Although we touch briefly on other products available on the platform, they are incidental to the topic at hand and are not discussed in detail.</p>      		 ]]></description>
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    	<item>
		<title>The LANSA Low Code Development Platform &#45; for mission&#45;critical Enterprise applications</title>
		<link>http://www.bloorresearch.com/research/inbrief/the-lansa-low-code-development-platform/</link>
		<pubDate>Mon, 14 Aug 2017 17:05:01 +0000</pubDate>
		<category>InBrief</category>
						<author>admin@bloor.eu (David Norfolk)</author>
		<dc:creator>David Norfolk</dc:creator>
				<guid isPermaLink="false">2344</guid>
		<description><![CDATA[
      	  		<p><span xss=removed>The part of the extensive LANSA product suite considered here is a high-productivity, low-code development platform ("Visual LANSA") which promotes rapid web and mobile development. It targets professional developers of mission-critical applications; it is not intended for "citizen developers" working in "shadow IT". By providing one language (which removes any need for JavaScript, HTML, Java, C#, AJAX or PHP skills) that can develop front-end to back-end automation, using IT to programme business processes as applications, with high productivity (and, thus, with the sort of rapid delivery that can effectively reduce the application backlog), it can help to reduce any incentive to indulge in shadow IT.</span></p>      		 ]]></description>
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		<title>Big data and the mainframe &#45; issues and opportunities</title>
		<link>http://www.bloorresearch.com/research/spotlight/big-data-and-the-mainframe-p1/</link>
		<pubDate>Wed, 09 Aug 2017 13:13:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2330</guid>
		<description><![CDATA[
      	  		<p><span xss=removed>This is the second edition of this spotlight paper. The first edition discussed big data - primarily analytic data - and how it could be leveraged alongside and within mainframe environments. This second edition extends that discussion to include the fact that it is becoming increasingly popular to offload functions such as real-time log analytics, to third party platforms such as Splunk (which is both a big data analytics platform and a security information and event management (SIEM) enabler), in order to support security and IT service functions. These are big data implementations in the same way that running something like sentiment analytics, on Hadoop, is; and have the same issues. </span></p>
<p><span xss=removed>The purpose of the current paper is therefore to examine these issues and, in particular, we focus on the issues that arise when organisations are integrating their mainframe system of record alongside big data implementations.</span></p>      		 ]]></description>
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    	<item>
		<title>DATPROF</title>
		<link>http://www.bloorresearch.com/research/indetail/datprof/</link>
		<pubDate>Wed, 09 Aug 2017 13:02:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
				<guid isPermaLink="false">2343</guid>
		<description><![CDATA[
      	  		<p>In this paper, we will discuss DATPROF and its test data management offerings. In particular, we will discuss DATPROF Subset and DATPROF Privacy: DATPROF's sub-setting and data masking tools, respectively. Note that while we are here considering DATPROF Privacy within the context of test data, the product is also suitable for use in<br>other environments where static data masking may be required.</p>      		 ]]></description>
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		<title>Governance for Spreadsheet Models</title>
		<link>http://www.bloorresearch.com/research/spotlight/governance-for-spreadsheet-models/</link>
		<pubDate>Mon, 07 Aug 2017 10:35:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>Spreadsheets are used for multiple purposes. One of the most common use cases is building and on-going use of models. These models could be of various types but the most frequent are financial models, actuarial models, budgetary models and the like, though engineering models of various types are also common. This paper discusses the governance of spreadsheets specifically when they are being used to create and deploy these and other sorts of models.</p>      		 ]]></description>
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		<title>Governance for Spreadsheet Models Apparity</title>
		<link>http://www.bloorresearch.com/research/white-paper/governance-for-spreadsheet-models-apparity/</link>
		<pubDate>Mon, 07 Aug 2017 10:30:00 +0000</pubDate>
		<category>White Paper</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2331</guid>
		<description><![CDATA[
      	  		<p>Spreadsheets are used for multiple purposes. One of the most common use cases is building and on-going use of models. These models could be of various types but the most frequent are financial models, actuarial models, budgetary models and the like, though engineering models of various types are also common. This paper discusses the governance of spreadsheets specifically when they are being used to create and deploy these and other sorts of models.<br><br>Further, this includes a section discussing how Apparity meets the requirements identified during our generic consideration of this space.</p>      		 ]]></description>
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		<title>Understanding data in hybrid cloud environments</title>
		<link>http://www.bloorresearch.com/research/spotlight/understanding-data-in-hybrid-cloud-environments/</link>
		<pubDate>Thu, 03 Aug 2017 10:15:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2341</guid>
		<description><![CDATA[
      	  		<p>The first question we address in this paper is what do we really mean when we talk about the hybrid cloud? What is the difference between a genuine hybrid deployment, as opposed to a siloed or heterogeneous approach. And having answered that question, what sort of data should reside on-premises or in the cloud, or in a (genuine) hybrid environment? When doesn't it matter? When does it matter? If it does matter, why does it? These are the sorts of questions that this paper addresses. There is a short section at the end discussing IBM's support for hybrid cloud environments (IBM sponsored this paper) but the bulk of the discussions are generic and not IBM specific. </p>      		 ]]></description>
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		<title>Overcoming the complexity gap &#45; the role of automation in optimising network performance and security</title>
		<link>http://www.bloorresearch.com/research/ebook/overcoming-the-complexity-gap/</link>
		<pubDate>Mon, 10 Jul 2017 17:33:00 +0000</pubDate>
		<category>eBook</category>
						<author>admin@bloor.eu (Fran Howarth)</author>
		<dc:creator>Fran Howarth</dc:creator>
				<guid isPermaLink="false">2340</guid>
		<description><![CDATA[
      	  		<p>The growing sophistication and pace of technology is creating challenges for security personnel-strapped organisations to keep up in the light of ever more determined and better resourced adversaries. Those technology advances include the rise in mobility and cloud computing, expanding use of virtualisation, the move to software-defined networking and microsegmentation, and the Internet of Things. This is creating a complexity gap that only looks set to get worse. Networks today look vastly different to those of just five years ago and a further sea change will be seen in the coming three to five years.<br><br>To overcome that gap, automation is essential. Deploying a network security management that automates manual functions will reduce errors and risk exposure, and enable greater productivity without the need to hire large numbers of scarce security professionals. It will vastly help in improving overall security postures and will help organisations to realise their governance and compliance objectives.</p>      		 ]]></description>
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		<title>Evolving uses of the kill chain framework &#45; using threat lifecycle management to defeat insider threats and ransomware</title>
		<link>http://www.bloorresearch.com/research/ebook/evolving-uses-of-the-kill-chain-framework/</link>
		<pubDate>Mon, 10 Jul 2017 16:55:00 +0000</pubDate>
		<category>eBook</category>
						<author>admin@bloor.eu (Fran Howarth)</author>
		<dc:creator>Fran Howarth</dc:creator>
				<guid isPermaLink="false">2337</guid>
		<description><![CDATA[
      	  		<p>The cyber kill chain framework has proven to be a great tool for helping to defend against a wide range of threats, from advanced targeted attacks to fraud. It is currently evolving to meet the needs of specific types of threats. The insider threat kill chain and ransomware kill chain discussed here show how it can be used by organisations in a range of circumstances. In all circumstances, the use of a threat lifecycle management platform, which itself has evolved from SIEM systems, will help organisations considerably in their fight against cyber criminals. It provides the automation that is essential for detecting and responding to threats in an efficient and effective manner. Combined with advanced capabilities that include artificial intelligence and machine learning, organisations of all sizes will be better placed to defend themselves.</p>      		 ]]></description>
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		<title>Data Masking 2017</title>
		<link>http://www.bloorresearch.com/research/market-update/data-masking-2017/</link>
		<pubDate>Fri, 02 Jun 2017 13:40:00 +0000</pubDate>
		<category>Market Update</category>
						<author>admin@bloor.eu (Philip Howard, Daniel Howard)</author>
		<dc:creator>Philip Howard, Daniel Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>With the forthcoming introduction of GDPR (general data protection regulation) the need to be able to anonymise data as a part of a data-centric approach to security is becoming more pressing. This Market Update compares the capabilities of different data masking vendors that provide anonymisation capabilities. In practice, in terms of the masking techniques that are supported, the market is relatively mature. However, there remain distinct differences between suppliers in terms of the sorts of data (structured, semi-structured, unstructured) that can be masked, the supported environments (especially NoSQL), and the ability to identify sensitive data accurately and with a minimum of false positives (and negatives). While the focus in this paper is on static data masking, both dynamic data masking and format preserving encryption (FPE) are also discussed.</p>      		 ]]></description>
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		<title>The Chief Data Officer: getting the basics right</title>
		<link>http://www.bloorresearch.com/research/spotlight/the-chief-data-officer-getting-the-basics-right/</link>
		<pubDate>Fri, 26 May 2017 09:55:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>What is the function of the Chief Data Officer (CDO)? In particular, what are the issues and problems that face a CDO, and which a CDO should be able to resolve, that are not within the compass of a CIO? In effect, why do you need a CDO? When do you need a CDO? What makes a CDO different? One set of answers to that is the business responsibility mentioned in the Wikipedia description and the whole question of what data is required and how it should be exploited. That is not what we will discuss in this paper. Here we are going to consider more fundamental issues. Before a CDO can think sensibly about what data the business might want to leverage, whether now or in the future, he or she is going to have to get a handle on the data assets that the company already possesses. In particular, these need to be discovered, understood, governed and secured, all of which are exacerbated by the scale and, especially, by the complexity of your data landscape.</p>
<p>In this paper, we are going to consider more fundamental issues. Before a CDO can think sensibly about what data the business might want to leverage, whether now or in the future, he or she is going to have to get a handle on the data assets that the company already possesses. In particular, these need to be discovered, understood, governed and secured, all of which are exacerbated by the scale and, especially, by the complexity of your data landscape.</p>      		 ]]></description>
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		<title>Tricentis Tosca TestSuite</title>
		<link>http://www.bloorresearch.com/research/indetail/tricentis-tosca-testsuite/</link>
		<pubDate>Fri, 26 May 2017 09:50:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
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		<description><![CDATA[
      	  		<p>In an increasingly agile world where deployment is becoming ever more challenging and time-to-market is declining, traditional testing is simply too slow to cope, in terms of both test creation and test execution. Continuous testing is becoming not just a nice-to-have, but a necessity. Comprehensive testing is becoming increasingly desirable, but many companies waste resources on redundant tests which only appear to increase coverage while actual risk coverage remains low. Most companies simply do not know how to achieve comprehensive test coverage and end up testing the same things over and over again, ending up with a massive amount of redundancy and overhead for little real gain. Typical figures are shocking: the average level of redundancy in enterprise test case portfolios is as much as sixty-seven percent, while the risk coverage averages only forty percent. What is needed is a risk-based approach to requirements and test generation that minimises the number of tests generated while providing a high level of risk coverage. <br><br>Unfortunately, achieving the right level of coverage with the right tests is not, on its own enough. Manual testing is just too slow and must be replaced by automation as much as possible.</p>      		 ]]></description>
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		<title>Blueprint and Storyteller</title>
		<link>http://www.bloorresearch.com/research/indetail/blueprint-and-storyteller/</link>
		<pubDate>Fri, 26 May 2017 09:45:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Philip Howard, Daniel Howard)</author>
		<dc:creator>Philip Howard, Daniel Howard</dc:creator>
				<guid isPermaLink="false">2311</guid>
		<description><![CDATA[
      	  		<p>Requirements are the bedrock upon which all software development and testing are founded. The biggest case of mismatches between what the user expected and what the software developers delivered is arguably caused by a failure to capture requirements adequately. And the second most important reason behind these mismatches is the use of tools that do not enable business users to work effectively with developers. Collaborative requirements capture and management tools should be obligatory, especially in large and complex environments. <br><br>Blueprint Software Systems has developed and marketed Blueprint, a requirements management product, for some years. In June 2016 the company introduced Storyteller which is specifically designed to address key issues IT organisations experience as they transition to agile approaches, and to act as a bridge to test automation environments.</p>
<p>This paper focuses on Storyteller plus particular elements of Blueprint that complement Storyteller.</p>      		 ]]></description>
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		<title>Managing Data Lakes</title>
		<link>http://www.bloorresearch.com/research/spotlight/managing-data-lakes-p1/</link>
		<pubDate>Wed, 24 May 2017 09:00:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2313</guid>
		<description><![CDATA[
      	  		<p>This paper discusses why data lakes need to be managed and the sorts of capabilities that are required to manage them. As it turns out the list is quite extensive. And this raises a problem: if you need six or eight different technologies to effectively manage a data lake then does it makes sense to look for so many best-of-breed solutions or would you be better off starting with a platform-based approach and only adopting best-of-breed solutions where that is absolutely necessary? This paper also considers the hidden costs involved in managing data lakes such as training, integration costs between tools and other elements that make up total cost of ownership.</p>      		 ]]></description>
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		<title>Clinical Correspondence Maturity &#45; an NHS cost&#45;management opportunity</title>
		<link>http://www.bloorresearch.com/research/white-paper/clinical-correspondence-maturity/</link>
		<pubDate>Tue, 23 May 2017 10:05:00 +0000</pubDate>
		<category>White Paper</category>
						<author>admin@bloor.eu (Paul Bevan, Simon Holloway, David Norfolk, Richard Rose)</author>
		<dc:creator>Paul Bevan, Simon Holloway, David Norfolk, Richard Rose</dc:creator>
				<guid isPermaLink="false">2336</guid>
		<description><![CDATA[
      	  		<p>The Business Issue facing the average NHS Trust today is the need to do "<em>more with less</em>". Changing demographics - population aging, and the tendency for people to live on into old age, in a state of (expensive) ill-health, rather than dying soon after retirement, are increasing the load on the NHS. This is happening as there are increasing pressures on resources (the promised "Brexit benefit" of £350 million a day seems not to have eventuated).</p>
<p>This White Paper spotlights a significant cost-management opportunity for a typical UK NHS (National Health Service) trust, and one that is comparatively low risk - a "no-brainer" for cost reduction together with service level improvements. In its essentials, it is about automating Clinical Correspondence, using digital recording, sophisticated Voice Recognition, and automated Workflows (as provided, for example, by an established vendor such as Winscribe). This leads to the more efficient utilisation (redeployment or reduction) of existing human resources and considerable savings in the time of expensive consultants and medical staff. Most importantly, it presents this in the context of increasing the operational maturity level of the Trust involved, which enables a 'capability of change' - this relates to the idea of a Mutable Trust, one that can respond to its changing environment in near real-time. Maturity ensures that any changes made do not reduce service levels and are 'sticky' (i.e. are maintained into the future), and continual maturity improvement extends this 'capability of change' to the Trust's operations generally.<br><br>This paper should be read by the Board of an NHS Trust and by change managers tasked with delivering cost reduction and operational improvements in the NHS. It will also be of interest to managers actually involved with delivering NHS services - it is presented with a very specific context in mind, but has a more general application. <br><br></p>      		 ]]></description>
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		<title>NHS Technologies &#45; Bloor&apos;s Framework for NHS Technology Maturity</title>
		<link>http://www.bloorresearch.com/research/market-review/nhs-technologies/</link>
		<pubDate>Mon, 22 May 2017 07:12:00 +0000</pubDate>
		<category>Market Review</category>
						<author>admin@bloor.eu (Paul Bevan, David Norfolk, Richard Rose)</author>
		<dc:creator>Paul Bevan, David Norfolk, Richard Rose</dc:creator>
				<guid isPermaLink="false">2335</guid>
		<description><![CDATA[
      	  		<p>This review document is not a conventional Bloor Market Update. It is a survey of available NHS technologies relevant to Bloor's study of NHS Process Maturity in the context (initially) of Clinical Correspondence and Bloor's Enhanced Clinical Correspondence Maturity Index (CCMI). Maturity is a question of Process; the understanding of what process you have; institutionalising process and sharing good practice across the organisation; process metrics; continual improvement of process based on key metrics; and, pro-actively managing process. However, process automation is usually key to achieving maturity and keeping it - making process maturity "sticky" - so the choice of technology can be an approximate indicator of process maturity. Although, of course, just buying the right technology doesn't guarantee maturity, it has to be used in a mature process, but it is unlikely that a high-maturity clinical correspondence process, for example, will use manual dictation and store correspondence in paper archives. <br><br>This Report will be of interest to practitioners trying to improve maturity in the NHS and to their managers.</p>      		 ]]></description>
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		<title>Test Data Management</title>
		<link>http://www.bloorresearch.com/research/market-update/test-data-management/</link>
		<pubDate>Wed, 03 May 2017 06:40:00 +0000</pubDate>
		<category>Market Update</category>
						<author>admin@bloor.eu (Philip Howard, Daniel Howard)</author>
		<dc:creator>Philip Howard, Daniel Howard</dc:creator>
				<guid isPermaLink="false">2327</guid>
		<description><![CDATA[
      	  		<p>It is worth detailing some major features that we expect from a Test Data Management (TDM) product. Firstly, it should be able to deal with sensitive data. That is, either the product needs to include data masking capabilities or it needs to be able to generate synthetic data, or both. Secondly, the solution should implement the principles of DevOps and support agile environments. This means putting as little strain as possible on database administrators and, in practice, this either means generating virtual copies of your source database(s) or running off a test data warehouse. In either case, the idea is to allow the re-provisioning of (amended) test data on demand, without having to go back to the production data or the administrators thereof. In effect, providing a self-service test data environment for developers and testers. Thirdly, you would like your TDM solution to integrate with other tools within the testing environment so that, for example, test data can be automatically provisioned to relevant test cases. Lastly, you would like your TDM solution to be not just representative of your real data but also to include outliers, boundary conditions and erroneous data that might not - almost certainly will not - appear in your production data. This Market Update compares TDM products on this basis.</p>      		 ]]></description>
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		<title>Best&#45;of&#45;breed test design automation</title>
		<link>http://www.bloorresearch.com/research/market-update/best-of-breed-test-design-automation/</link>
		<pubDate>Wed, 03 May 2017 06:30:00 +0000</pubDate>
		<category>Market Update</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2321</guid>
		<description><![CDATA[
      	  		<p>It is not immediately clear what the space discussed in this paper should be called. The tools evaluated here certainly automate the generation of test cases, but some of them do so in only a limited fashion while many of them do rather more than that. We have therefore opted for the rather more nebulous "test design automation". Moreover, we have restricted ourselves to those products that we consider to be best-of-breed since there are a great many tools and products that we might have included in this Market Update. Two potential categories of product have been omitted from this report. Firstly, tools that we believe to have been left behind by emerging market trends. For example, we regard keyword-based approaches to generating test cases as table stakes. That isn't to say that we have completely ignored keyword-based products (Micro Focus' Silk Central, for example) but what we are generally looking for is more advanced capabilities, especially those that are model-based. Secondly, we have omitted products that focus on testing within systems (engineering) environments as opposed to those that concentrate on software development.</p>      		 ]]></description>
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		<title>Zizo</title>
		<link>http://www.bloorresearch.com/research/indetail/zizo/</link>
		<pubDate>Fri, 28 Apr 2017 14:32:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2329</guid>
		<description><![CDATA[
      	  		<p>Zizo provides analytics as a service with its solution targeted at all classes and sizes of organisations. While on-premises deployments are possible, typical users employ Zizo within a managed cloud environment. A major feature is that Zizo provides everything you might need with respect to analytics or business intelligence: the database in which to store the data, facilities to transform Executive summary existing (internal and external) data and load it into that database, data preparation functionality for blending the data, query and analytic capabilities to explore the data, built-in slice and dice and reporting capabilities, and dashboards in which to represent the results. The company provides its own front-end tool - Insight - for data visualisation, which has been specially tuned to work with large data sets. Connectivity options are also provided to support third-party tools such as Yellowfin, Qlik and Tableau. </p>      		 ]]></description>
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		<title>Concentric Analytics for IoT</title>
		<link>http://www.bloorresearch.com/research/spotlight/concentric-analytics-for-iot/</link>
		<pubDate>Thu, 23 Feb 2017 15:33:00 +0000</pubDate>
		<category>Spotlight</category>
						<author>admin@bloor.eu (Philip Howard)</author>
		<dc:creator>Philip Howard</dc:creator>
				<guid isPermaLink="false">2322</guid>
		<description><![CDATA[
      	  		<p>The Internet of Things can best be imagined as a concentric series of capabilities that start at the edge with sensors and devices of various kinds, whose data is collected, aggregated and filtered through one or more gateways until the data is presented centrally for operational and analytic purposes. Analytics of one sort or another are typically taking place across this ecosystem and there are a number of good reasons - discussed in this paper - why it will make sense to use the same analytic software across this environment.</p>      		 ]]></description>
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		<title>TurnKey Solutions</title>
		<link>http://www.bloorresearch.com/research/indetail/turnkey-solutions/</link>
		<pubDate>Thu, 23 Feb 2017 15:30:00 +0000</pubDate>
		<category>InDetail</category>
						<author>admin@bloor.eu (Daniel Howard, Philip Howard)</author>
		<dc:creator>Daniel Howard, Philip Howard</dc:creator>
				<guid isPermaLink="false">2319</guid>
		<description><![CDATA[
      	  		<p>This is a technical evaluation of Turnkey Solutions' offering. The company is active in the testing space and it has three major features that set it apart from other automated testing tools. It is application-aware: it learns from your application and detects differences between your application and your tests. Secondly, it is data-driven: tests can be built in the abstract and then populated with data to create multiple paths through your application. Lastly, it utilises (patented) Evergreen Automation that monitors your application for changes and, when a change occurs, it shows you the changes and automatically updates your tests and related data management. The company is a partner of CA and resells products such as Agile Requirements Designer, with which its own products integrate.</p>      		 ]]></description>
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