Data Management

Blend, cleanse and prepare data for analytics, reporting or data modernization efforts

Data Management
Jim Harris 0
Data steward is a tough role to play

In my previous post I explained that even if your organization does not have anyone with data steward as their official job title, data stewardship plays a crucial role in data governance and data quality. Let’s assume that this has inspired you to formally make data steward an official job title. How

Data Management
Dylan Jones 0
The causal link between education and data quality

Here on the Data Roundtable we've discussed many topics such as root-cause analysis, continual improvement and defect prevention. Every organization must focus on these disciplines to create long-term value from data quality improvement instead of some fleeting benefit. Nowhere is this more important than the need for an appropriate education strategy, both in

Data Management
Leo Sadovy 0
Big Silos: The dark side of Big Data

The bigness of your data is likely not its most important characteristic. In fact, it probably doesn’t even rank among the Top 3 most important data issues you have to deal with.  Data quality, the integration of data silos, and handling and extracting value from unstructured data are still the most

Analytics | Data Management
Suzanne Clayton 0
Be proactive. Be a trailblazer with data.

For many industries, big data analytics have opened numerous doors for more employees to be groundbreaking and to challenge the corporate status quo. Prior to big data technologies, risk taking behaviors were primarily reserved for provocative souls who stretched organizational boundaries to disrupt industries, such as airline revenue management. There were winners and losers

Data Management
Wilson Raj 0
Data privacy doesn't have to be scary

Marketers are walking a tightrope today with data privacy issues: Data can simultaneously bring customers and brands together and further drive them apart. Recent data breaches, potential changes in data-privacy legislation and regulations loom large as customer expectations concerning marketing data continue to rise. As a result, today’s complex data

Data Management
Anne Belder 0
Hadoop: the game-changer in banking

At most banks, data is stored in separate databases and data warehouses. Customer data is stored in marketing databases, fraud analyses are done on transactional data, and risk data is stored in risk data warehouses. Oftentimes even liquidity, credit, market, and operational risk data is stored separately as well. Bringing

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