The data computation layer in between the data persistent layer and the
application layer is responsible for computing the data from data persistence
layer, and returning the result to the application layer. The data
computation layer of Java aims to reduce the coupling between these two
layers and shift the computational workload from them. The typical
computation layer is characterized with below features:
Ability to compute on the data from arbitrary data persistence layers, not
only databases, but also the non-database Excel, Txt, or XML files. Of all
these computations, the key is the computation on the commonest structured
data. Ability to perform the interactive computations among various data
sources uniformly, not only including the computation among different
databases, but also calculation between the databases and non-database data
sources. The coupling... (more)
What is IOE? I=IBM, O=Oracle, and E=EMC. They represent the typical high-end
database and data warehouse architecture. The high-end servers include HP,
IBM, and Fujitsu, the high-end database software includes Teradata, Oracle,
Greenplum; the high-end storages include EMC, Violin, and Fusion-io.
In the past, such typical high performance database architecture is the
preference of large and middle sized organizations. They can run stably with
superior performance, and became popular when the informatization degree was
not so high and the enterprise application was simple. With the ... (more)
Recently a development team met some difficulties in data source computation
when developing iReport reports. After the use of esProc for cross database
computation, the problem is resolved.
This is a project payment progress report, as part of a project management
system. It's based on an Oracle database. The reports needs to present the
project name, payment amount, contract value, payment progress (in
percentage), and name of the project manager, etc., for all ongoing projects.
Amount these the first 3 items contributes to the difficulties met by the
Note t... (more)
Enterprises always have various data sources, for instance, CRM system may
use SQL Server, sales reports adopt Excel, ERP applies Oracle database. When
it comes to actual business analysis, enterprises usually need to conduct
interactive computation, including filter, group, etc among various data
environments. But data Interaction between multiple data sources are not easy
to realize with some traditional statistical computing tools. In order to
solve such kind of problems, esProc which adapts to various data environments
comes into being.
Support of various data sources is an... (more)
Recently, I read "Why Big Data Projects Fail" by Stephen Brobst. I can’t
agree more with his opinions which exposed the problem I’ve been worried
about. In this article, I am going to further discuss this topic to remind
the enterprises to beware of falling into such pitfall of failure.
Let’s have a look on a positive example. As a successful enterprise in
leveraging big data, how does Google make use of the big data?
1. Collect the row data, capture the contents of each website, e-mail, or
Cookie, and extract the key information.
2. Create the complex syndetic index for this inf... (more)