Database Reference
In-Depth Information
# Copy the file from local workstation to the Blob
container
Set-AzureStorageBlobContent -File $fileName -Container
$containerName
-Blob $blobName -context $destContext
Integration Thoughts for Big Data
Your big data solution should not exist in isolation. To get the most benefit
out of the solution, it should not be built for just a couple of data scientists
who will use it to do analysis in which they publish sporadic reports of their
findings. If it does exist in isolation, you are not extracting the value out of it
that it contains.
Your big data solution needs to be integrated into the rest of your analytics
and BI infrastructure. When you integrate your solution with your existing
data warehouse and BI infrastructures, more corners of your organization
can learn to gain insights from the additional data brought into your
organization.
NOTE
Don't worry, you've done data integration before. Your big data solution
is now just another data source, albeit with possibly more data,
different data types, and new structures that you've never dealt with
before. But those are challenges, not barriers.
You likely already have a data warehouse environment that is a
subject-oriented reporting environment tightly constrained around
dimensional data that drives reports your organization relies on. The data
that lives in this data warehouse is likely driven from your transactional
environments.
Your new big data environment now houses additional data that likely
wasn't cost-effective to store in your existing data warehouse (perhaps
because the data was either too big or too complex for efficient storage).
Most solutions will include having a subset of subject matter experts who
will be hitting this data directly using the skills learned in this topic to
extract new insights. But inside of this data is a subset of data that could
