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An enterprise guide to big data in cloud computing

Big data has made big waves in the cloud market, with top providers rushing to offer services. Discover what technologies are out there, as well as best practices to manage large volumes of data.


Big data is no longer just the future -- it's the present. The retail industry, for example, uses big data to better understand its customers, and to optimize internal business processes. Scientists are now able to crunch large amounts of data at a more rapid pace for research. The benefits of big data have expanded beyond the enterprise, too, helping individuals track personal health based on data from wearable devices.

Big data in the public cloud allows organizations to tap into some of these benefits without having to invest the time, money and IT staff needed for an on-premises deployment. The use of big data in cloud computing also helps enterprises process, analyze and manage large, varied data sets more quickly and efficiently. To start, organizations should evaluate the data they have and determine the insights they want from it. Next, they should evaluate the big data services and management tools from top cloud providers, such as Amazon Web Services (AWS), Azure and Google.

Follow this guide on big data in cloud computing to get started.

1Big data options in cloud-

Evaluate cloud models, providers for your big data project

Before you pursue big data in cloud computing, evaluate which cloud environment will best fit your needs: public, private or hybrid cloud. Consider how sensitive your data is and review your compliance requirements -- if they're strict, private or hybrid cloud may be the better option. For public or hybrid cloud users, the next step is to evaluate which public cloud provider suits your needs. The top three cloud providers, AWS, Azure and Google, all have big data services and management tools. Compare what each provider offers for storage, databases, analytics and other big data tools.


Which cloud environment is right for my big data project?

Choosing the wrong environment for your big data project can negatively impact costs and make it tough to meet technical demands. See if public, private or hybrid cloud best meets your big data needs. Continue Reading


Explore these database options for your big data platform

Once you choose a database model -- such as SQL, NoSQL or Hadoop -- for your big data platform, explore the cloud options available that will work best with the model you select. Continue Reading


Evaluate big data services from AWS vs. Azure vs. Google

The three top cloud providers, AWS, Azure and Google, all offer competitive big data services. Take a close look at each to determine the best fit for your data. Continue Reading


Dive deeper into Azure's big data services

Navigating through Azure's vast lineup of big data services can be difficult. Use this list of key terminology on Azure's big data services to help guide you. Continue Reading


Get acquainted with Google big data services

Like Azure, Google has a long lineup of big data services, ranging from database to analytic tools. To help you choose, here's a list of key terms to know. Continue Reading


Compare Azure SQL Data Warehouse vs. AWS Redshift

Many providers offer cloud data warehousing services. Examine the differences between two common AWS and Azure services -- SQL Data Warehouse and Redshift -- before making your decision. Continue Reading

2Manage and analyze big data-

Choose the right big data management, analytics tools

After choosing a cloud service provider, the next step is to evaluate management, monitoring and other tools for big data in cloud computing. While providers offer some native tools within their services, be sure to also evaluate third-party and open source tools that can help you manage large amounts of data in the cloud. Hadoop, a Java-based programming framework, is a popular tool to process large data sets and also includes MapReduce, a component that enables distributed processing of massive, unstructured data sets across compute clusters. In addition, enterprises should consider various tools and methods to keep big data secure.


Determine if MapReduce or Spark is right for your big data

MapReduce and Spark are popular options for enterprises looking to process big data in the cloud. Compare these two services, including performance and other factors, to see which one is right for you. Continue Reading


How can I use Hadoop for big data in the cloud?

There is a lot involved to process big data, and Hadoop can help with its support of distributed data storage and processing tasks. But there are alternatives to consider, including Hydra, Zillabyte and Stratosphere. Continue Reading


A closer look at Amazon Elastic MapReduce, Kinesis Firehose

AWS brings a lot to the big data table, including Elastic MapReduce and Kinesis Firehose, two services that can help users scale, distribute and process vast amounts of data. Continue Reading


Use the right VM instances, GPUs to support big data

Moving big data to the cloud isn't a one-step process. Reduce challenges and maintain performance with GPUs and VM instances with enough DRAM, compute cycles and disk I/O. Continue Reading


Overcome Apache Hive challenges in AWS

Organizations use Apache Hive, an open-source data warehouse tool, to handle difficult analytical jobs. But the tool can present certain challenges, especially when using an older version, in AWS. Continue Reading


Follow these best practices to secure big data

The Cloud Security Alliance recognizes the growth of big data and offers some best practices to keep your data secure, including policy-based encryption and tagging. Continue Reading

3Big data in the news-

Read up on recent big data and cloud news

Top providers AWS, Azure and Google dominate news around big data in cloud computing. These vendors introduce and update big data services at a rapid pace to lure in enterprise customers. While Google has years of experience due to its search engine practice, and recently scored Spotify as a customer, AWS and Azure have also made steady progress. AWS, for example, offers a large amount of data storage choices, and Azure has unique services, such as its Cortana suite for advanced intelligence capabilities.


Azure fleshes out big data tools

Azure continues to add new features to its big data service, such as SQL Data Warehouse, a second-generation, fully managed and cloud-based data warehousing service. Continue Reading


Google upgrades database services to benefit big data

Google pushes forward to make its big data services as robust as possible with upgrades to its database services, including the latest version of Cloud SQL, and the release of Cloud Bigtable and Cloud Datastore. Continue Reading


AWS aims to disrupt with QuickSight BI service

AWS QuickSight BI seeks to provide fast and simple analytics capabilities for big data, but has fallen a bit short compared to the competition. Still, experts see great potential for the service in the coming years. Continue Reading


Google reels in a big fish with its big data services

Google has struggled to attract enterprises to its cloud platform, but it scored a big customer, Spotify, in February 2016 because of its big data services. Continue Reading

4A quiz on big data in cloud-

See how much you know about big data in cloud computing

An important part of the learning process is to quiz yourself on the subject. Take this test to see if you know the big data basics.

Take This Quiz

5Big terms for big data-

Prepare for big data in the cloud with this glossary

When trying to learn big data basics, an excellent place to start is to learn the key terminology. Build a sound foundation for your big data and cloud computing knowledge with these definitions.

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Thanks for the Stratosphere tip. We're currently figuring this out as we've recently shifted our big data to stratoscale's cloud. It's been a rough transition, very challenging, but at the end we're all better IT personnel because of that.