Shankar RamaNathan, Author at Perficient Blogs
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Shankar RamaNathan

Shankar RamaNathan is a Senior Enterprise Architect with 25+ years of experience in successfully developing and implementing IT strategy and Information Governance ( Master Data Management, Metadata Management, Data Quality and Data Governance) programs.

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Building a successful Searchandizing strategy…

What is searchandizing? Obviously search in the context of merchandising. Retailers have taken this technique to a different level. Constant price pressures and competition from online retailing has spurred the innovation in this area both in terms of tools, approach and overall strategy. In the early dot com days several online retailers have built custom […]

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Reasons for chronic Data Quality issues…

Many companies have invested millions in building a successful BI / EDW and are investing in advanced analytics for the future. But the mystery remains about the data quality. Though glaring DQ issues might be contained through constant backend data corrections or through exception handling, many organizations still faces the challenge of poor data quality. The reason Data […]

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Digital Trends and Impacts

Digital Transformation has been happening for a while, what is different now compared to earlier years of digital transformation, is the factors which determine the Transformation. Who is changing the game ? the speed and the volume of information available etc. The change is fast because it is just not only the companies who changes the customer engagement […]

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Sales Intelligence impact on bottom-line…

In my earlier blog, Salesforce and Predictive Analytics, I was making a point why Salesforce has taken a keen interest in predictive analytics software.  Salesforce has turned the market inside out by taking the complexities of IT and infrastructure delays, and not to mention out-of-the-box implementation features, easy enough for small companies to implement with minimal budget and external help. […]

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Salesforce and Customer Master

Salesforce is a boon for companies which can’t take a number and wait for IT to prioritize the implementation. However if adequate data architecture planning is not done, it can end up as a siloed application with Data Quality issues. Many companies don’t have the time to engage the Enterprise team for CRM implementation besides […]

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What Salesforce’s Backing of Predictive Analytics Firm Means

You might have seen the news that Salesforce and Microsoft invested in the predictive analytics (Insidesales.com) company to the tune of $65M. Salesforce is the leader of cloud / SaaS platform in the world, why are they investing in predictive analytics? Barring any obvious financial reasons, it is very clear that ERP serves the purpose of […]

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Analytical Talent Gap

As new companies embark on the Digital Transformation leveraging Big Data, key concerns and challenges get amplified especially for the near term before the technology and talent pool supply adjusts to the demand. Looking at the  earlier post Big Data Challenges, the top 3 concerns were: Identifying the Business value/Monetizing the Big Data Setting up the […]

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Big Data Challenges

As companies start adapting to handle Big Data, the challenges still remains. Barring the obvious applications, the challenges of getting the value out of the new-found data continues to be on the top of the list. ROI’s and potential revenues are yet to be realized. As the technology and the usage becomes more sophisticated we will […]

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Managing Data in the Digital Transformation Era

Managing data has been a challenge irrespective of the size of the company. Last couple of decades most of the companies invested in leveraging the Enterprise Data through variety of initiatives like Enterprise Data Warehouse and Business Intelligence. If we divide the enterprise information usage in the last 2 decades, primarily they fall into the […]

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Big Data, Big Confusion

  Everyone wants a piece of Big Data action whether you are part of Product Company, Solution provider, IT, or Business user. Like every new technology, Big Data is confusing, complex and intimidating. Though the idea is intriguing, the confusion begins when the techies start taking sides and tout the underlying tools rather than solution. […]

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Information Governance Trends for 2015

The year 2014 just ended. 2015 is already looking like another year of data intensive initiatives.  Looking at the initiatives and investments happened in 2014, Big Data will continue to be on the top, and so does the cloud. Enterprise Data investment continues to grow as the laggards in technology are warming up to the Information […]

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Analytics in the Digital Transformation Era

Successful Enterprises compete on many capabilities ranging from product excellence, customer service and marketing to name a few. Increasingly the back office / Information Technology (IT) is becoming a strategic player in the Digital Business Model which supports these key capabilities. In other words back office/IT Capability itself is becoming a differentiator. All of the […]

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Reference Architecture – Cloud MDM for Salesforce

In my earlier post Why MDM should be part of CRM Strategy I discussed the importance of having a MDM strategy along with the CRM initiative. Proliferation of cloud CRM solutions like Salesforce is a blessing and it can also be an IT nightmare, if it is not managed properly.  In many companies Salesforce implementation […]

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Cloud MDM – Reference Architecture for Public Cloud Platform

Moving the MDM deployment to a cloud platform involves several considerations ranging from technical gotchas to getting the internal buy-in. Getting the buy-in is a different topic of discussion – see my earlier posts on Data Governance. The advantages of moving to cloud eliminates some of the administrative and server farms related maintenance tasks but […]

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Cloud MDM – are we getting closer?

As Master Data Management matures and becomes a standard application within the enterprise architecture landscape, variations of cloud offerings are slowly emerging. Many companies are not even aware of these solution offerings. You can broadly classify the types of cloud offerings into 3 categories. There are key advantages and disadvantages in pursuing these architectures. The […]

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Key strategies for Data Quality

In numerous client engagements, we have witnessed that Data Quality (DQ) is a never-ending battle. At many companies,  IT fixes and re-fixes the data rather than develop solutions and manage applications. DQ is not confined to IT, but maintaining that quality requires effort from all data users, especially those at the business end. Building a […]

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Lambda Architecture for Big Data – Quick peek…

In the Big Data world Lambda architecture created by Nathan Marz is a standard technique applied to solve many predictive analytics problems. This architecture effectively delivers the streaming data and batch data to combine the past information with the current changes, producing a comprehensive platform for predictive framework. Lambda Architecture On a very high generic […]

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Bootstrapping Data Governance – Part II

As I mentioned in my earlier post, building the vision for Data Governance happens through multiple meetings, interactions and discussions at various levels. Depending on the company culture and type of industry, progress may end up being faster or slower. Leadership in building the awareness and linking the business issues which can be solved through […]

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Bootstrapping Data Governance – Part I

A lot has been said and written about Data Governance (DG) and the importance of having one. However it is still a mystery for many companies to create an effective DG. Based on our experience majority of the companies in their early stages of DG fall into one of these areas: Had too many false […]

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