What are some of they key things that cause big data projects to fail?

It mostly starts with unrealistic expectations and the wrong people doing the job. Big data is not an extension or the logical extension of data warehousing. It's much more complex. This often creates an ability gap in companies whose big data team is made up of database administrators. This why a data engineer or data scientist is often worth their higher salary. Adding big data to a person’s skill set is not easy and may not be possible for everyone. Data engineers and data scientists already have the skill set. Plus, even for those who are capable of learning these skills, it takes time and resources, which slows momentum on many projects.