Best Practices for Master Data Management

Mastech InfoTrellis offers best of breed Master Data Management Services enabling Customers to harness the power of their Master Data. Mastech InfoTrellis has successfully delivered Master Data Management Projects time and again over the past decade.

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Best Master Data Management Strategy

Mastech InfoTrellis offers best of breed Master Data Management Services enabling Customers to harness the power of their Master Data. Mastech InfoTrellis has successfully delivered Master Data Management Projects time and again over the past decade.

IBM InfoSphere Master Data Management

IBM InfoSphere Master Data Management (MDM) manages all aspects of your critical enterprise data, no matter what system or model, and delivers it to your application users in a single, trusted view. Provides actionable insight, instant business value alignment and compliance with data governance, rules and policies across the enterprise.

Cloud Customer 360 For Sales Force

Informatica Cloud Customer 360 for Salesforce eradicates duplicate, inaccurate, and incomplete account and contact records. It provides clean, trusted data, increases Salesforce user adoption, and boosts ROI.

Informatica Intelligent Master Data Management

A complete master data management solution addresses the critical business objectives digital organizations face. Informatica MDM offers the only true end-to-end solution, with a modular approach to ensure better customer experience, decision making and compliance.

IBM PIM For Manufacturing

Establish a single view of product information for strategic business initiatives with IBM Product Information Management solution. IBM PIM solution enables Service Oriented Architecture, provides a flexible data model, aligns to existing business processes and is scalable to suit to the growing product landscape of an organization.

Contact:
9390 Research Blvd., Suite 330
Austin, TX 78759
United States
Phone: +1-512-358-1396
Website: http://www.infotrellis.com

InfoTrellis to be Acquired by Mastech Digital

Toronto, Ontario, Canada – July 7, 2017: InfoTrellis, Inc., a Toronto-based  Data Management & Analytics company, today announced that it has entered into a definitive agreement under which Mastech Digital, Inc. (NYSE: MHH), a leading Digital Transformation Services provider, will acquire InfoTrellis’ services division. The demand for Digital Transformation consulting services is growing rapidly, as more Fortune 1000 companies are funding digital transformation initiatives to reinvent how they do business.  Data & analytics is at the heart of every digital transformation strategy and our combination will bring together two differentiated companies – both with global brand recognition and complementary service offerings – and a unique value proposition to offer expertise and scalability in digital transformation consulting.

The acquired business, to be branded as Mastech InfoTrellis, will offer project-based consulting services to customers in the areas of Master Data Management, Data Integration, Big Data and Customer Intelligence Management (Customer 360), and at the same time strengthen Mastech Digital’s digital transformation services capability. InfoTrellis’ industry-wide recognition for its thought leadership and depth in data management & analytics, as well as proven global delivery expertise, will enhance the growth opportunities of the combined entity.

“Mastech Digital has global brand recognition and is highly respected in the IT industry, and InfoTrellis is very excited to join them,” said Mahmood Abbas, CEO and Co-founder of InfoTrellis.  “I am confident that our strengths in delivering consulting services in data management & analytics, combined with Mastech Digital’s scale and proven experience in providing IT staffing and digital transformation services, will offer a unique value proposition in the market of scalable consulting teams with deep expertise.”

The transaction is valued at USD $55 million, with USD $35.7 million paid in cash at closing and USD $19.3 million deferred over an earn-out period .

InfoTrellis and Mastech Digital expect to realize several synergies from the combined enterprise:

• Ability to participate in larger digital transformation deals
• Opportunity to cross-sell broader range of service offerings to existing and future customers of both businesses
• Larger scale, improved operational efficiencies and expanded global delivery model
• Better economies of scale from shared support services integration

 “We began transforming Mastech into a digital transformation services company a year ago when we launched our new name ‘Mastech Digital’ and recast our service offerings,” said Vivek Gupta, President and CEO of Mastech Digital. “The acquisition of InfoTrellis will be a significant milestone in that journey. I am delighted with the capabilities InfoTrellis brings to the Mastech Digital family and am excited about creating a combined organization that will deliver world-class services around Data Management & Analytics in its expanded portfolio of digital transformation services.”

 The combined entity will have augmented scale, expanded global delivery capability, and deeper leadership strength.  “The integration will advance our vision of addressing the wider challenges faced by our clients in adopting Big Data and Advanced Analytics,” said Sachin Wadhwa, COO and Co-founder of InfoTrellis.  “We believe the combination of Mastech Digital and InfoTrellis will have a meaningful impact in the way Data Management and Analytics consulting is delivered by us.“ 

Mahmood Abbas and Sachin Wadhwa will continue to play the leadership role in the combined entity.

The product division of InfoTrellis has been spun off as a separate company called AllSight, Inc., and Zahid Naeem, one of the Co-founders of InfoTrellis, has moved to the AllSight company. “Our vision for InfoTrellis consulting has always been to provide premium data management and analytics consulting services for our clients,” said Zahid Naeem.  “This partnership with Mastech Digital is a major milestone in continuing with that vision. We are also looking forward to a strong partnership between the combined entity and AllSight Inc., as Customer Intelligence Management, or a Customer 360, is a critical software system to deliver upon a digital transformation strategy.”  

InfoTrellis has over 200 associates globally, a customer-base of more than 40 blue chip customers in North America, offices in Toronto (Canada) and Austin (Texas, U.S.), as well as a global delivery center in Chennai (India).  Mastech Digital has nearly 1,300 associates globally, a customer-base of over 300 companies, seven offices across the US, as well as a delivery center in New Delhi (India).

The acquisition is subject to customary closing conditions and is expected to close in July 2017.

About Mastech Digital

Mastech Digital (NYSE MKT: MHH) is a national provider of IT services focused on solving its customers’ digital transformation challenges. The Company’s IT staffing services span across digital and mainstream technologies while its digital transformation services include Salesforce.com, SAP HANA, and digital learning services. A minority-owned enterprise, Mastech Digital is headquartered in Pittsburgh, PA with offices across the U.S. and India. For more information, visit www.mastechdigital.com.

About InfoTrellis

InfoTrellis is a Canada-based Information Management Consulting and Technology Services Company that provides project and consulting services in Master Data Management, Data Integration, Customer Intelligence Management, and Big Data.

Which is the best master data management company in USA?

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

Best master data management company in USA

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

Learn more at, http://www.infotrellis.com/master-data-management/

InfoTrellis Master Data Management Company Texas

InfoTrellis Master Data Management Company Texas

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

Read for more information at, http://www.infotrellis.com/master-data-management/

What are some of the must-have features in an Master Data Management (MDM) product?

1. Delivery Methodology – Our Smart MDM™ methodology is a result of our many years of experience working with clients on complex MDM programs. This methodology offers a common sense, multi-phased approach based on parts of Rational Unified Process (RUP) and Agile development methodologies. It blends deliverables with accountability and requires customer-focused teams to collaborate to deliver a high-quality MDM solution. It provides tested methods to ensure success for MDM projects.

Advantages of Smart MDM™:

• Value is delivered early and often
• Greater ability to respond to change
• Collaboration encouraged between business and IT
• Tried and tested approach on multiple projects
• Client satisfaction managed more closely

2. Solution Accelerators – Based on our years of experience implementing MDM programs, we built a number of solution accelerators to speed up our services delivery. These include:

• Templates for various phases of a project
• Automation tools for testing
• Quick test data preparation
• Audit tools to review our solution
• Codebase for quality

Some of the tools include:

• ITLS Service Tester used for functional and regression testing
• Test Data Generator
• Validator
• AutoUI which is used to automate DSUI testing

What is Master Data Management Software?

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

Which is Good Master Data Management Agency in USA?

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

Which are the top Master Data Management Agency?

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

 Master Data Management Agency

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

Retailers’ Successes and Struggles with Big Data in 2014

Recent research by McKinsey and the Massachusetts Institute of Technology shows that companies that inject big data and analytics into their operations outperform their peers by 5% in productivity and 6% in profitability. Our experience suggests that for retail and CPG companies, the upside is at least as great, if not greater.”
Peter Breuer, director of McKinsey & Co.’s retail practice in Germany
With November half over and 2015 starting to peek at us over the horizon, we decided it was time to take a look at a few examples of what retailers have been using big data for in 2014. Here are three examples of use cases for Big Data in retail that have emerged in the last year, followed by a few InfoTrellis predictions about what will happen next in the new year when it comes to the evolution of how companies are implementing their Big Data strategies.

Macy’s

Personalized Marketing

The main goal for Macy’s CEO, Terry Lundgren, is to offer more localized, personalized and smarter retail customer experience across all channels. They use Big Data among others to create customer-centric assortments. They analyse a large amount of different data points, such as out-of-stock rates, price promotions, sell-through rates etc. and combine these with SKU data from a product at a certain location and time as well as customer data in order to optimize their local assortments to the individual customer segments in those locations.

 In addition to that, Macy’s gathers, and of course analyses, a vast amount of customer data ranging from visit frequencies and sales to style preferences and online & offline personal motivations. They use this data to create a personalized customer experience including customized incentives at checkouts. Even more, they are now capable of sending hyper-targeted direct mailings to their customers, including 500,000 unique versions of a single mailing. The results are compelling; Macy’s e-commerce division alone has witnessed a growth of over 10% and an overall annual revenue growth of 4% with the use of Big Data Analytics.
 (Macy’s Is Changing The Shopping Experience With Big Data Analytics)
 
Personalizing the user experience is a ubiquitous use case for big data, so it’s exciting to see a retailer actually implementing the technology to accomplish and prove out the value of this marketing strategy. Four percent growth is nothing to scoff at; this number represents millions of dollars on pure profit they didn’t have before. For companies that still believe they can accurately segment their hundreds of thousands of customers with fewer than a hundred profile archetypes, this is an undeniable piece of proof that they may need to consider getting on the bandwagon if they don’t want those millions of dollars to be coming out of their share of the customer’s spending habits.

What’s more, this is a front-and-center application of big data that is highly visible to the shopper. Whether or not they can articulate the difference in quality of experience they get from a retailer that uses it and a retailer that doesn’t, it’s a difference they can intuitively feel and will definitely react to by rewarding one store with loyalty over the others.

Once companies start pulling social data and combining it with internal customer data, their targeting and micro-segmentation capabilities will enable even more uniquely tailored marketing and customer experiences. So long as companies remember that the purpose of this data-collection is to minimize friction and irrelevant messaging for their customers and never to manipulate them or milk them for money like a mindless herd, the consumer stands only to benefit from the evolution of this practice.
For this reason, my prediction is that this will be a big differentiator in the coming years as the companies that experiment with it first (i.e. the early adopters) get better and better, making the gap increasingly noticeable to the end consumer. There will be a scramble by the companies that lagged behind to try to catch up, and this will represent a big shift for the retail industry’s established best practices in much the same way the idea of the loyalty program and the digital storefront did.

Read More http://www.infotrellis.com/retailers-successes-and-struggles-with-big-data-in-2014/

Top Reasons an MDM Implementation Fails

I often become involved in an organization’s MDM program when they’ve reached out to InfoTrellis for help with cleaning up after a failed project or initiating attempt number X at achieving what, to some, is a real struggle. There can be a lot of reasons for a Master Data Management implementation failing, and none of them are due to the litany of blame game reasons that can be used in these scenarios.  Most failures arise from common problems that people just were not prepared for.
Let’s examine some of the top reasons MDM implementations fail. In the end they probably won’t surprise you, but if you haven’t experienced it yet you will be better prepared to face them if they happen.

Underestimating the work

I am starting with this one because it leads to many of the others, and is a complex topic. It seems like a simple thing to estimate the work but there are a lot of aspects to an MDM project that aren’t obvious that can severely impact timelines and your success.

“It’s just a project like any other”

Let me start by saying MDM is not a project, it’s a journey, or at the very least a program.
Most organizations thinking about implementing MDM are large to global companies. Even medium sized companies that started small and experience growth over time have the same problems as their global sized piers.  While the size of the chaos in a global company may seem much larger, they also have far more resources to throw at the problem than their smaller brethren.
If we stick to the MDM party domain as a point of reference (most organizations start here with MDM), the number of sources or points of contact with party information can be staggering. You may have systems that:

• Manage the selling of products or services to customers
• Manage vendors you deal with or contract to
• Extract data to data warehouse for customer analytics and vendor performance
• HR systems to manage employees who may also be customers
• Self-service customer portals
• Marketing campaign management systems
• Customer notification systems
• Many others

A lot of large organizations will have all of these systems, each having multiple applications, and often multiple systems responsible for the same business function. So by now you are probably saying, yes I know this, and…?  Well your MDM “project” will need to sit in the middle of all of this, and in many cases since many of these systems will be legacy mainframe based systems, you will need to be transparent as these systems won’t be allowed to be changed.
MDM can be on the scale of many of the transformation programmes your organization may be undertaking to replace aging legacy systems and moving to modern distributed Service Oriented Architecture based solutions.

Big Bang Never Works

Now that we have seen the potential size of your MDM problem, let me just remind you that you can’t do it all at once. Sure you can plan your massive transformation programme and execute it – but if you have ever really done one of these, you know it’s a lot harder than it seems and that the outcome is usually not as satisfying as you expected it to be.  You end up cutting corners, blowing the budget, missing the timelines, and de-scoping the work just trying to deliver.
What is one of the typical reasons this happens on your MDM transformation project?

You Don’t Know What You Don’t Know

You have all these systems you are going to integrate with and in many cases you are going to need to be transparent in that those systems may not know they are going to be interacting with your new MDM solution. You are going to need to know things like:

• What data do they use?
  • How often?
  • How much?
  • When?
• Do they update the data?
  • How often?
  • How?
  • What?
• Do they need to know about changes made by others?
  • How often is the change notice required?
  • Do they need to know it’s changed, or what the change was?

This type of information seems pretty straight forward. I haven’t told you anything you probably didn’t know, but, when you go to ask these questions, the answer you will mostly likely often get is:

“I don’t know.”

Ok, so the documentation isn’t quite up to date, (I am being kind), but you are just going to go out and find the answer. Which leads to the next problem.

Not Enough Resources

So this is an easy problem to solve. I’ll hire some more business analysts, get some more developers to look at the code, get some more project managers to keep them on track.  Seems like a plan, and on the surface it looks like the obvious answer, (ignoring how hard it is to locate available quality IT people these days), but these aren’t the resources that are the problem.

You don’t have enough SMEs.

The BA’s, developers and others are all going to need time from your subject matter experts.  The subject matter experts are already busy because they are subject matter experts.  There typically aren’t enough of them to go around, and if you have a lot of systems to deal with, you are facing a lot of IT and business SME’s.
What your SMEs bring to the table is intellectual property. Intellectual property is critical to the success of your implementation.  You will need the knowledge your SMEs bring on your various systems, but there is another kind of intellectual property that you are going to need and can be tied to a very lengthy process.

Read More http://www.infotrellis.com/top-reasons-an-mdm-implementation-fails/

InfoTrellis Expands Executive Team with Addition of Former IBM Exec, John Gairhan

InfoTrellis hires veteran sales executive from IBM as it positions itself to lead the customer data management market into the next generation.

InfoTrellis, an innovative provider of Customer 360 software, announced the hire of John Gairhan as Vice President of Sales. The addition further enhances the company’s experienced executive leadership team, all of whom understand the customer data and analytics market and how it is evolving to address organizations’ most pressing use cases.

As VP of Sales, Gairhan will leverage his 25 years of experience in sales, strategy, marketing and development of enterprise software to help solve clients’ highest priority customer big data problems. According to Forbes and Forrester, 48 percent of big data projects currently underway are focused on customer analytics, yet 88 percent of customer data is ignored for analysis because it is not easy to access in various silos. Gairhan will assist clients in addressing those customer data challenges to achieve Customer 360 and power the omnichannel experience.

InfoTrellis is a pioneer in the analytics and data management industry. InfoTrellis’ flagship product, AllSight, integrates all data – external and internal – to deeply understand customers, learn more about them, and provide an actionable 360-profile to all business users. Powered by machine learning, pre-built analytics and contextual matching to build the customer 360 from granular pieces of data, AllSight also enriches that record with customer intelligence and insights. Marketing and sales users access this enhanced customer data to personalize digital marketing and sales campaigns, while services utilize it to power personalized omnichannel customer care.

“We are unique in that our customer data system is purposely built to solve today’s biggest data challenges and maximize the value of data,” said Sachin Wadhwa, COO and co-founder at InfoTrellis. “The success of InfoTrellis is due to our deep technical expertise and industry knowledge, both of which will benefit from Gaihran’s experience as a former big data worldwide sales leader and promoter of open source technologies such as Apache Spark and Apache Hadoop. His insight will no doubt enable us to take InfoTrellis to the next level.”

The majority of Gairhan’s industry experience has been focused on data management. He led the worldwide Big Data sales team at IBM and worked as a consultative big data seller, partnering with Fortune 500 companies to define and execute their big data strategy and architecture while leveraging their existing IT investments. He has also held leadership positions in MDM strategy and marketing.

“For the past 25 years I have evangelized emerging data and analytics technology,” said Gairhan. “I have a passion to help organizations become more intelligent about their customers. My approach and strategy perfectly align with InfoTrellis’ vision and I am confident our exceptional executive team will reimagine the customer data and analytics market.”

About InfoTrellis

Based in Toronto, Canada, InfoTrellis has been a leading information management consulting and technology company since 2007, serving data-driven companies with the expertise and products required in today’s data-heavy world. As a pioneer in the big data, data integration and master data management market, InfoTrellis offers AllSight ConnectID and Veriscope in its comprehensive suite of data management products. AllSight ConnectID gives companies a complete Customer 360 view of each customer to facilitate an effective omnichannel strategy. Veriscope provides insight into the quality and usage of Master Data for successful Master Data Management and governance.Contact more.

Common Sense is very uncommon

“Effort is important, but knowing where to make an effort makes all the difference!”

A few days ago, at the end of a very intense release, one of our long term clients asked what is the secret behind our team’s high quality testing effort, despite the very aggressive timelines and vast scope of work that she sets up for us. She was very much interested in understanding what we do different from the many large SI’s she has used in the past, who according to her were always struggling to survive in a highly time-conscious and fast changing environment. We went back with a presentation to the client’s delivery team, which was highly appreciated by one and all. This blog provides a gist of the practices that we follow to optimize our testing effort.

The fundamental principles that help us in managing an optimum balance between Scope, Time and Costs while ensuring high quality delivery are Build for Reuse, Automation and Big Picture Thinking.

To understand these principles better, let us consider the real project that we just concluded for this specific client. This project had three major work streams – MDM, ETL and BPM. The duration of the project was 8 months and was executed using the InfoTrellis Smart MDM^TM methodology. In total, 3 resources were dedicated for testing activities, 1 QA Lead and 2 QA Analysts. Of the allocated 8 months (36 weeks), we spent 6 weeks on discovery & assessment, 6 weeks on scope & approach & 4 weeks on the final deployment. The remaining 20 weeks, that was spent on Analysis, Design, Development and QA, was split into 3 iterations with durations of 7, 7 and 6 weeks respectively. The QA Activities in this project were spread over these 3 iterations.

 Build for Reuse:

While every project and the iterations within a project will have its unique set of requirements, team members and activities, there will always be few tasks that are repetitive and will remain the same across iterations and across projects. Test Design Techniques, templates for test strategy, test cases, test reporting, test execution processes are some assets which can be heavily reused.

Being the experts in this field, we’ve built a rich repository of assets that can be reused across different projects. During the 1^st iteration, the team utilized the whole 4 weeks which included some time for tweaking the test assets to suit the specific project needs. Due to the effort put in the 1^st iteration to set up reusable assets, the team was able to complete the next two iterations in 2 weeks each.On the whole, we were able to save 2 weeks’ [6 man-weeks] worth of efforts in the next two iterations with the help of reusable assets.

Automation:

The task of testing encompasses the following four steps.

• Creation of test data
• Converting data to appropriate input formats
• Execution & validation of test cases
• Preparation of reports based on the test results

With 500 test cases in the bucket, the manual method would have taken us around 675 hours or 17 weeks approximately to complete the testing. However by using the various automation tools that we have built in-house such as ITLS Service tester, ITLS XML Generator, ITLS Auto UI and ITLS XML Comparator and many others we were able to complete our testing within 235 hours. The split of the effort is as follows:

The automation set up & test script preparation took us 135 hours approximately. But by investing time in this effort, we saved around 440 hours or 11 weeks even with executing 3 rounds of exhaustive regression tests. This was a net saving of 33 man weeks for the QA team.

  

Big Picture Thinking: 

One day a traveler, walking along a lane, came across 3 stonecutters working in a quarry. Each was busy cutting a block of stone. Interested to find out what they were working on, he asked the first stonecutter what he was doing and stonecutter said “I am cutting a stone!” Still no wiser the traveler turned to the second stonecutter and asked him what he was doing. He said “I am cutting this block of stone to make sure that its square, and its dimensions are uniform, so that it will fit exactly in its place in a wall.” A bit closer to finding out what the stonecutters were working on but still unclear, the traveler turned to the third stonecutter. He seemed to be the happiest of the three and when asked what he was doing replied: “I am building a cathedral.”

 The system under test had multiple work streams like MDM, ETL and BPM that were interacting with each other and the QA team was split to work on the individual work streams. Like the 3^rd stonecutter, the team not only knew about how their work streams were expected to function but also about how each of them would fit into the entire system.

Thus we were able to avoid writing unnecessary test cases that could have resulted due to duplication of validations across multiple work streams or due to scenarios that may not have been realistic when considering the system as a whole. This is captured in the table below.

Our ability to identify the big picture thus saved us 128 hours or 3.2 weeks. To avoid such effort going down the drain, we get our QA leads to participate in the scope & approach phase so that they are able to grasp the “Big Picture” and educate their team members.

Conclusion:

Using our testing approach, we saved more than 16 weeks [48 man weeks] of QA effort and thus were able to complete the project in 8 months. Without our approach, this project could have gone easily for over 12 months. This also meant that we did not require the services of a team of 6 InfoTrellis resources [1 Project Manager, 0.5 Architect, 0.5 Dev Lead, 1 Developer, 1 QA Lead and 2 QA Analysts] for 4 additionalmonths i.e. 24 man months and avoided the many client resources who would have been on this project otherwise.

What we have described in this blog is only common sense which is well known to everyone in our industry. However common sense is very uncommon. At InfoTrellis, we have made full use of this common sense and are able to deliver projects faster and with better quality. This has helped our clients realize value from their investments much sooner than anticipated and at a much lower total cost of ownership.Contact More.

Initiate your Data Governance

Data Governance is an important and imperative area for Enterprises that want to realize full value from the data available with them.  InfoTrellis’ Data Governance Methodology follows a multi-phased iterative approach with 4 stages – Initiate, Define, Deploy and Optimize. This article lists the important considerations that are part of the Initiate stage of our Data Governance Methodology.

The Debate– Small or Big? The very first step of Data Governance is also the most ambiguous for most enterprises. The most common debate is whether to start an independent Data Governance program across enterprise or to start with specific problem at hand and then scale big. Most enterprises that are successful with Data Governance start small with a specific domain or business area to solve a data issue and then expand. The few enterprises that aim for enterprise wide Data Governance, break their program in small iterative steps to achieve success. So whatever the approach, – small or big – having small iterative steps is the key. It is critical to resolve this debate and finalize on the strategy before embarking on further activities.

Maturity Assessment – Assessing the current state of information management is essential to understand why things went wrong and how they can be fixed. Clients can adopt any of the leading Maturity Standards for their Data Governance Program including the one from InfoTrellis. These standards are referenced to mark the current maturity level of a particular business area. It is a normal scenario to have different maturity levels for different business areas of an enterprise. We suggest that specific prescriptive roadmap be defined considering the individual maturity level of each area. The maturity assessment needs review after each iterative deployment of Data Governance policies.

Data Governance Roadmap– The roadmap defines the steps to be taken to reach the desired state of Data Governance. This can be specific to a business area at the start and can be refined based on each of the incremental Data Governance deployments.

Secure Sponsorship – A compelling business case highlighting the business problem, its impact on revenue and cost and how it can be resolved by Data Governance, is important for getting the attention of executives and the subsequent sponsorship. Many Data Governance programs lose steam mid-way due to inadequate sponsorship. Executives have to continuously send messages to the team, educating and reinforcing the importance of achieving data governance goals.

Assign an effective Program Manager – Data Governance programs are complex programs requiring top notch process and people skills and needs continuity. Hence identifying the right program manager with clearly defined roles and responsibilities is very important for a successful program. We have seen many programs suffer due to ambiguous or frequently changing Program Managers.

In conclusion, each enterprise begins its data governance program differently. But addressing each of the above considerations and activities proactively helps setup a path to success.

Check out the Part 2 of this 4 part series on Data Governance from InfoTrellis – Define your Data Governance
Please send us a note with your queries and feedback. Contact more.

Master data management Services by InfoTrellis

Master data management

 

Master data management

InfoTrellis has a rich legacy in Master Data Management (MDM) and is founded by the team that has been shaping the industry since 1999. When you work with InfoTrellis, you’re dealing with the industry’s most knowledgeable service provider and have access to the most experienced MDM resources available.

We provide strategic consulting and tactical expertise to help clients define and deploy Master Data Management (MDM) solutions in service of their business objectives. InfoTrellis has expertise in all editions of IBM MDM, including MDM Server Standard Edition (f.k.a Initiate Master Data Services), MDM Server Advanced Edition, MDM Server Collaboration Edition (f.k.a PIM) and has worked on Customer, Product, Location, Vendor and Account domains. We were part of the team that architected the first multi-domain MDM Server covering the Product and the Account domains and were one of the first companies to implement IBM’s Reference Data Management (RDM) solution.

For more information visit us at, http://www.infotrellis.com/master-data-management/