John Haddad

John Haddad

Balancing Opportunity and Risk in Big Data

Informatica conducted a recent big data survey of 600 IT and business professionals in North America, Europe and the Asia-Pacific region. The results found in the report entitled: Balancing Opportunity and Risk in Big Data – A Survey of Enterprise Priorities and Strategies for Harnessing Big Data show that big data has clearly moved beyond all the hype with nearly 70 percent of organizations of all sizes considering, planning, testing, or running big data projects.  While the majority of organizations are focused on big transaction data and analytics, the survey shows a strong interest in social media information, unstructured content, industry-specific data, and machine-generated information from sensors and devices. (more…)

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Posted in Big Data, Informatica 9.5 | Tagged | Leave a comment

Informatica 9.1 Supports Best Practices For Agile Data Integration

Informatica supports Agile Data Integration for Agile BI with best practices that encourage good data governance, facilitate business-IT collaboration, promote reuse & flexibility through data virtualization, and enable rapid prototyping and test-driven development.  Organizations that want to successfully adopt Agile Data Integration should standardize on the following best practices and leverage Informatica 9.1 to streamline the data integration process, improve data governance, and provide a flexible data virtualization architecture.

1. The business and IT work efficiently and effectively to translate requirements and specifications into data services (more…)

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Posted in Data Governance, Data Integration, Data masking, Informatica 9.1, Master Data Management | Tagged , , , , , , , , , | 1 Comment

Agile Data Integration Maximizes Business Value In The Era Of Big Data

Adopting Agile may require a cultural shift and in the beginning can be disruptive to an organization.  However, as I mentioned in Part 1 of this blog series, Agile Data Integration holds the promise to increase chances of success, deliver projects faster, and reduce defects.  Applying Lean principles within your organization can help ease the transition to Agile Data IntegrationLean is a set of principles first explored in the context of data integration by John Schmidt and David Lyle in their book on Lean Integration.  First and foremost Lean recommends an organization focus on eliminating waste and optimizing the data integration process from the customers’ perspective.  Agile Data Integration maximizes the business value of projects (e.g. Agile BI, Data Warehousing, Big Data Analytics, Data Migration, etc.) because you can get it right the first time by delivering exactly what the business needs when they need it.  Break big projects into smaller more manageable deliverables so that you can incrementally deliver value to the business.  Agile Data Integration also recommends the following: (more…)

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Posted in Data Services | Tagged , , , , , | Leave a comment

Waterfalls Can Be Dangerous. Try Agile Data Integration For Agile BI.

Most organizations will admit that it takes much too long for the business to get the data they need.  IT projects take too long to deliver — from the time business requirements are defined until the project go-live.  With traditional waterfall-style project management there is a tendency to throw requirements and deliverables over the fence to the next phase so that by the time the project is delivered the business has moved on and the requirements may have changed.  It is a well-known fact that most IT projects fail from the customers’ perspective.  That doesn’t mean the project was not delivered but instead means that the project failed to deliver the expected business value. (more…)

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Posted in Telecommunications | Tagged , , , | 1 Comment