Database Reference
In-Depth Information
replace their existing enterprise BI environment. We are just adding new
data sets to enable them to pull additional information to add value to
their existing reports and provide a deeper level of analysis than what they
would normally be able to perform. These existing tools (for instance, Excel
and Power BI from Microsoft) provide leading-edge capabilities to take
advantage of all we are doing with these new tools.
The ecosystem that we cover in this topic is providing an additional data
platformandasetofcapabilitiesfordeveloperstoserviceadditionaltypesof
dataatvolumesthatwerepreviouslymuchmoredifficult(andinsomecases
prohibitive). With these limitations removed, consumers can now reach a
new level of information collection collaboration and management.
Power Users
Power users are going to be some of the most advanced users of these new
solutions. They can be doing everything from custom model creation to
creating their own Hive tables and writing their own Pig scripts.
These users will demand the most assistance with the actual tools and more
assistance with where data is located, how it is being loaded into the system,
how they access it, and what kind of metadata is available. Power users will
work closely with the developers as the developers build out the functional
pieces of the platform, which the power users will then integrate into the
system to take something to the next level.
Data Developers
Data developers will be one of your largest and most demanding of all the
audiences. In fact, you might be in this category yourself.
Data developers are going to be in charge of everything from sourcing data,
to bringing it into the HDFS, loading it into nonrelational data sources such
as Mongo DB, and creating Hive tables for users to connect to. And then,
most likely, they will be responsible for developing export functionality to
dump the subsets of valuable data that users find during analysis out to the
format that can then be integrated into the enterprise BI system.
It is this life cycle of identifying data, making it available for exploration,
reviewing the results of that exploration, and then taking subsets of
value-addeddatainbuildingintegrationprocessesthatwillkeepthenewbig
data developer very busy. This is an extremely exciting time for developers.
