Databases Reference
In-Depth Information
7.10
Apply your knowledge
Sally works in an information technology department with many people involved in
the software development lifecycle (
SDLC
).
SDLC
documents include requirements,
use cases, test plans, business rules, business terminology, report definitions, bug
reports, and documentation, as well as the actual source code being developed.
Although Sally's department built high-quality search solutions for their business
units, the proverb “The shoemaker's children go barefoot” seemed to apply to their
group.
SDLC
documents were stored in many formats such as MS Word, wikis, spread-
sheets, and source code repositories, in many locations. There were always multiple
versions and it wasn't clear which versions were approved by a business unit or who
should approve documents.
The source code repositories the department used had strong keyword search, yet
there was no way users could perform faceted queries such as “show all new features in
the 3.0 release of an internal product approved by Sue Johnson after June 1.”
Sally realized that putting
SDLC
documents in a single NoSQL database that had
integrated search features could help alleviate these problems. All
SDLC
documents
from requirements, source code, and bugs could be treated as documents and
searched with the tools provided by the NoSQL database vendor. Documents that had
structure could also be queried using faceted search interfaces. Since almost all docu-
ments had timestamps, the database could create timeline views that allowed users to
see when code was checked in and by what developers and relate these to bugs and
problem reports.
The department also started to add more metadata into the searchable database.
This included information about database elements and their definitions, list of
tables, columns, business rules, and process flows. This became a flexible metadata
registry for an official reviewed and approved “single version of the truth.”
Using a NoSQL database as a integrated document store and metadata registry
allowed the team to quickly increase the productivity of the department. In time, new
web forms and easy-to-modify wiki-like structures were created to make it easier for
developers to add and update
SDLC
data.
7.11
Summary
In the chapter on big data, you saw that the amount of available data generated by the
web and internal systems continues to grow exponentially. As organizations continue
to put this information to use, the ability to locate the right information at the right
time is of growing concern. In this chapter, we've focused attention on showing you
how to find the right item in your big data collection. We've talked about the types of
searches that can be done by your NoSQL database and the ways in which NoSQL sys-
tems make searching fast.
You've seen how retaining a document's structure in a document store can increase
the quality of search results. This process is enabled by associating a keyword, not with
a document, but with the element that contains the keyword within a document.
