August 20, 2014
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Database Section Index

Develop Faster with the Laravel PHP Framework

Laravel is an increasingly popular PHP framework that can help you develop better, more sustainable code for a shorter amount of time. Read on to see what features it has to offer.

Business Intelligence – An Overview

Anoop Agarwal discusses the fundamentals of Business Intelligence (BI) and various data Warehouse design approaches. In this first article of the series, he shares how Big Data is different from traditional BI.

Writing Code that Writes Code

Every environment has its share of tedious, time-consuming but brain-dead code that’s required to get this or that working as it should. Tedious and time-consuming tasks are what computers do best. Why should you have to? See how the Microsoft T4 Templates make this possible.

How to Implement Database Relationship in Hibernate

The crux of the relational database management system is in the idea of establishing relationship among entities. Discover how Hibernate allows you to model association between entities from Java code, without bothering with the SQL.

Data Modeling Is Like Building A Boat

The effort put into data modeling is relative to the size of the project. Starting with a proper set of data models allows enhancements as the business needs grow and change.

Big Data: Practical Tips for ETL Testing

Big Data represents all kinds of opportunities for all kinds of businesses, but collecting it, cleaning it up, and storing it can be a logistical nightmare.

Getting Started with Azure HDInsight

Vipul Patel takes a look at Azure HDInsight, a service used to manage Hadoop clusters on Azure, Microsoft’s cloud computing platform.

Data Quality for a Modern Data Warehouse

Use data quality services (DQS) for cleansing and matching source data via business rules.

Using the ORM Tool in a Simple JDBC Program

Learn how ORM (Object Relational Mapping) can help map objects into a database as if you were no longer working with records of the relational model but objects in an object oriented model.

Working with the JDBC RowSet API

The RowSet interface is an extension of JDBC ResultSet and is a part of the javax.sql package. Read on to learn what RowSet is all about and how to implement it in Java.

Creating Data Centric Applications with JSP Servlet

JSP, Servlet and JDBC are a popular combination for creating dynamic web pages and applications with extensive data processing. Read on to learn more.

Top 7 Open-Source JSON-Binding Providers Available Today

Learn how to convert Java objects to JSON format, save it to a file, and then convert it back to an object.

Manipulating a Database with JDBC

Learn how to manipulate database records with the help of the Java Database Connectivity (JDBC) API.

To Create Fool-Proof Analytic Apps, Make It Easy for Your Developers

How do you deploy big data applications organization-wide to leapfrog competition, win the hearts of customers, and drive revenue by drawing well-informed, real-time conclusions?

JDBC Application Design Consideration

JDBC acts as a translator between Java applications and the native language of a database. Learn how the JDBC driver paves the way into the application design consideration of database programming in Java.

Database, Application, and Version Control and Everything In Between

Developers, team leaders, or R&D managers have a lot to gain by making their DBAs more productive.

XML Processing in Java EE 7

Manoj Debnath provides an overview of how to parse XML documents using JAXB, SAX, and DOM.

Six Features Key to Choosing a Data Validation Provider

Learn six of the most important features that a data validation service provider should offer.

Using Second Level Caching in a JPA Application

Learn how to improve the performance of an application that uses the Java Persistence API, by modifying the second level cache mode settings.

Manage Concurrent Access to JPA Entity with Locking

Learn how to handle concurrent access to entity data, and the locking strategies available to JPA API.

Understanding Big Data: The Hadoop Environment with BI Integration

Big data platforms and ecosystems emerged from the need to efficiently handle data volumes, velocities, and varieties that had not previously existed.

10 Facts about Hadoop

In today’s technology world, Big Data is a hot IT buzzword. To mitigate the complexity in processing large volumes of data, Apache developed Hadoop – a reliable, scalable and distributed computing framework. Read on to learn more.

Understanding Big Data Persistence

Learn about new data persistence technologies including NOSQL and NewSQL databases as well as about CAP theorem, useful data access patterns, and good practices applicable to enterprise application programming with Big Data.

Understanding Big Data Processing and Analytics

Learn about Big Data processing techniques addressing, but not limited to, various BI (business intelligence) requirements such as reporting, batch analytics, online analytical processing (OLAP), data mining, text mining, complex event processing (CEP), and predictive analytics.

Understand The High-Availability and Scalability Challenges with Big Data

Today, developers interested in Big Data can easily be lost in the jungle of numerous new technologies. Get a clear view on the Big Data technology landscape and learn to pick the most suited techniques for your Java software projects.

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