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.
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
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
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 can be problematic because it is often related to how an application is functioning. Continue Reading
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
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.
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
Learn about the next steps in big data trends for the enterprise in 2014. Continue Reading
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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.
There is a shift taking place in the business world, as big data in marketing empowers customers over companies. Continue Reading
Researchers and business users alike analyze big data in order to glean insights as to what customers actually want and need. Continue Reading
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.
At Big Data Techcon 2014, Software field engineer Max de Marzi makes a case for enterprise graph searches using the Neo4j database. Continue Reading
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.
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. A graph database is essentially a collection of nodes and edges. Each node represents an entity and each edge represents a relationship between two nodes. Continue Reading