Consider this…eBay’s “Singularity” Teradata warehouse exceeds 40 petabytes. According to eBay, the company’s data volumes are 50+ terabytes per day in new incremental data, processing 50+ petabytes
and tens of millions of queries per day, with 99.98% availability and more than 50 petabytes of online storage.
Data is valuable. Data is plentiful. Data is complex. Data is in flux. Data is fast moving. Capturing and managing data is challenging.
So, if you are a senior leader in a Fortune 2000 company. How do you structure your group to deliver effective BI, Analytics or Big Data projects? Do you have the right structure, toolset, dataset, skillset and mindset for analytics and Big Data?
Organizing for effective BI, Analytics and Big Data is becoming a hot topic in corporations. In 2012, business users are exerting significant influence over BI, Analytics and Big Data decisions, often choosing analytics and visualization platforms and products in addition to/as alternatives to traditional BI platform (reporting and visualization tools).
Interested in slicing, dicing, measuring, and analyzing data for customer and business insights?
According to a recent survey by Bloomberg, 97% of companies with revenues of more than $100 million are using some form of business analytics, up from 90% just two years ago.
While businesses have embraced the idea of fact-based decision-making, a steep learning curve remains. Only one in four organizations believes its use of business analytics has been “very effective” in helping to make decisions. Data is not just ignored but often discarded in many organizations as the business users can’t figure out how to extract signal from data noise.
However, it took until 1980s when decision support systems (DSS) became popular and mid 1990s for BI started to emerge as an umbrella term to cover software-enabled innovations in performance management, planning, reporting, querying, analytics, online analytical processing, integration with operational systems, predictive analytics and related areas.