Essential Guide

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An architect's guide: How to use big data

This essential guide shows how organizations are using big data and offers advice for IT professionals working with the technology.


Employees in organizations of all sizes can be faced with the daunting task of figuring out how to use big data and how to best manage it. Some IT professionals are tasked to use technology such as graph databases to crunch large volumes of data. Other developers need to be able to use tools like Hadoop to build systems capable of handling varying flows of data.

This guide brings together a range of stories that highlight examples of how to use big data, management techniques, trends with the technology, and key terms developers need to know.

1The cloud and big data-

Techniques for working with big data and the cloud

What is big data? How should it be used? These are two questions people commonly ask when they begin working with large volumes of data. While use cases are evolving, there are some tips and tricks that can be gleaned from success stories.

The following is a collection of articles going over the basics of working with big data.


What is big data?

Get answers to frequently asked questions about what big data is, why it can be a problem and how big data tools will be part of the solution. Continue Reading


How big data and cloud based analytics fit together

Organizations are handling more and more data all the time, and a big problem is figuring out how to find an important piece of information in peta-bytes of big data. How can it be done? Cloud based technologies that can burst and grow are becoming the standard solution. Continue Reading


AWS Big Data Solutions overcomes common challenges

Achieving an affordable database solution that is both scalable and performant has always been a challenge, but Amazon has put scalability and performance within the reach of all sizes of business with their NoSQL solutions that have grown out of their Dynamo based big data systems. Continue Reading


How data grid technology can help wrangle big data

Many organizations are finding that current IT setups cannot meet modern demands, and in some instances, using data grid technologies can help. Continue Reading


Data persistence: What big data and cloud app developers should know

Data persistence can be problematic because it is often related to how an application is functioning. Continue Reading


How to decide between REST and SOA for big data apps

When designing big data applications, an important consideration is whether to use SOA or RESTful APIs to connect big data components and services to the rest of the application. Continue Reading

2Using Hadoop-

Popular tools for working with big data

It's difficult to discuss how to use big data and managing large volumes of data without discussing Hadoop, a Java-based framework. Megacorporations like Google and IBM have capitalized on the technology, but that doesn't mean smaller companies don't stand to benefit from it as well.

Read on for technical advice about working with Hadoop.


How to reap the benefits of Hadoop with MapReduce 2.0

YARN represents the biggest architectural change in Hadoop since it's inception over seven years ago. Now, Hadoop goes beyond MapReduce to provide scheduled processing while simultaneously processing big data. Continue Reading


Where YARN fits in to Hadoop 2.0's success

MapReduce has matured, and so has Hadoop, and together under the umbrella of YARN, these powerful technologies are working together better than ever to deliver faster and more flexible big data solutions to the enterprise. Continue Reading


Be on the lookout: Hadoop, big data trends for 2014

Learn about the next steps in big data trends for the enterprise in 2014. Continue Reading

3Big data in marketing-

Benefit from harnessing big data

Long gone are the days of marketers scratching their heads to determine ways to use big data to their advantage. Organizations of all sizes are learning the benefits of being able to analyze big data and turn that information into a powerful resource to reach consumers. With this movement comes the need for IT professionals to know how to build systems able to wrangle large volumes of data.

The following is a collection of articles that highlight the basics of using big data in marketing.


How big data in marketing passes control from companies to consumers

There is a shift taking place in the business world, as big data in marketing empowers customers over companies. Continue Reading


Advice for using high-performance computing to analyze big data

Researchers and business users alike analyze big data in order to glean insights as to what customers actually want and need. Continue Reading


How to use big data management tools to meet consumer demand

Organizations are taking advantage of big data management tools as applications are required to handle a growing volume of data. Continue Reading

4Graph database use cases-

Make visual representations with big data

Implementing graph databases is one example of the ways organizations have learned to make meaningful use of big data. While the technology has its roots in social media, there are practical uses for graph databases that extend beyond Facebook. From dating sites to online retailers, the use cases are extensive.

Read on to learn more about big data and graph databases.


FAQ: Building a Facebook graph search using Neo4j database

At Big Data Techcon 2014, Software field engineer Max de Marzi makes a case for enterprise graph searches using the Neo4j database. Continue Reading


Graph database use cases beyond social media

While the most commonly known graph database use cases involve social media, it's not the only market to make use of the technology. Continue Reading


How graph searches and big data databases can be practical for enterprises

Software field engineer Max De Marzi explains why graph searches and big databases can be of practical use to the enterprise. Continue Reading


Common big data terms

This glossary provides common terms related to big data.


Big data

Big data is an evolving term that describes any voluminous amount of structured, semistructured and unstructured data that has the potential to be mined for information. Continue Reading


Big data analytics

Big data analytics is the often complex process of examining large and varied data sets -- or big data -- to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions. Continue Reading


Big data management

Big data management is the organization, administration and governance of large volumes of both structured and unstructured data. Continue Reading


Graph database

A graph database, also called a graph-oriented database, is a type of NoSQL database that uses graph theory to store, map and query relationships. Continue Reading



Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. Continue Reading



MapReduce is a core component of the Apache Hadoop software framework. Continue Reading



NoSQL is an approach to database design that can accomodate a wide variety of data models, including key-value, document, columnar and graph formats. NoSQL, which stand for "not only SQL," is an alternative to traditional relational databases in which data is placed in tables and data schema is carefully designed before the database is built. Continue Reading

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