All organizations, no matter how big their budget, must overcome barriers in order to realize value from data faster. Those that have historically experienced centralized, IT-centric BI implementations must transition to flexible environments that embrace the increased use of self-service technologies.
Augmenting the conventional EDW design with Hadoop and Hive can help optimize your EDW by expanding usability, improving performance, improving results, and reducing overall costs.
When numerous diverse data platforms are integrated for multiple use cases, it is called a hybrid data ecosystem (HDE), a concept invented and popularized by Enterprise Management Associates (EMA) in 2012. An HDE provides options for rapidly diversifying data and its business use. Despite the extreme complexity and challenges, users are succeeding with HDEs. This TDWI Checklist Report drills into the data requirements of the HDE with a focus on the role of data virtualization.
The growing adoption of cloud computing and software-as-a-service (SaaS) is merging with easier-to-use business intelligence and analytics tools to allow more users to interact with and analyze data. This Checklist Report discusses seven recommendations to help organizations be successful sooner in enabling a data-driven culture through visual, easier-to-use business analytics.
Read this e-book to find out what it means to be driven by data and what it takes to transition to such a culture.
Modern marketers are capturing success with an arsenal of advances in data management, software automation, and customer analytics that enable a single view of the customer. New sophisticated practices in omnichannel marketing leverage that view so marketers can serve burgeoning numbers of customers and channels. This Checklist Report drills into the data requirements of modern digital marketing, with a focus on the single customer view and omnichannel marketing.
Organizations need a strategy for a modern data platform that can support users who need more than traditional BI and OLAP provide but don’t have the specialized skills of advanced data scientists. This Checklist focuses on six key considerations for modern data platforms that enable more users to benefit from big data through easier to use, visual big data analytics.
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