Some Realities of Big Data

The critical, business aspect of analytics must be built in-house. This work cannot (must not) be outsourced.
Analytics-drive mindset is a deep, organization-wide, culture change. This will take years to develop.
Prediction is the easy part. Actionable insights are of real value.
You can (and must aim to) analyze the whole population. Sample is old school and (almost) obsolete.
Missing data is ok. Machine learning algorithms can work with gaps.
Machine learning algorithms will be incorrect in the beginning. They will improve in accuracy as they get trained with more data.
You will never have all the data (you think) you need.
You will never be able to analyze all the data at your disposal.
Not all predictions will be repeatable, scaleable.
There is more value to 3 different data-sets of say, 100,000 records each, than one big set of 10 million records.