Archive for the ‘Big Data’ Category

 

Big Data Can Knock Down Technical Barriers in the Boardroom

Wednesday, February 5th, 2014 by

The boardroom plays an important role in the ongoing development of an organization. Filled with executives and partners of all types, this room is the place where most decisions about a company’s future are made. Traditionally, discussions about the trajectory of enterprise programs were built around old conversations and past experiences, which guided decision-makers to either fund or kill prospective projects, depending on how rewarding managers believed certain initiatives would be in the long run.

Big data should knock down technical barriers in the boardroom

Big Data can knock down technical barriers in the boardroom

Today, some companies are embracing similar mentalities, which isn’t necessarily helping them, especially as new technological and operational trends emerge within the enterprise. Other firms are taking a more innovative approach and embracing the tectonic shifts happening within the IT landscape. In the past, IT movements were generally ignored by the boardroom because these projects were considered too technical, which meant that most employees were unaware of the direction of IT. The Big Data phenomenon has changed all of that.

Why bring data into the boardroom?
Businesses of all sizes and industries are quickly realizing that information is the key to success. Although this ideal has been reinforced in the past, the repercussions of not using data as a guide are becoming more widely understood.

Boardroom-level decision-makers used to base their expectations on gut feelings. Doing so was sometimes beneficial, especially when executives were highly experienced and aware of what was happening within their companies and competing firms; however, there was no effective way to guarantee their beliefs were accurate until it was too late to change their minds. Instead of following this antiquated approach to decision-making, executives can now use information to their advantage.

The digital world of today is fueled by a massive increase in available information because almost every activity carried out on a smartphone, tablet, or other computing device leaves a trail of data crumbs. By gathering these scraps of information and analyzing their trajectory, organizations can essentially predict the future and build strategies to maximize return on virtually any investment.

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How to Easily Deploy MongoDB in the Cloud

Monday, February 3rd, 2014 by

GoGrid has just released it’s 1-Button Deploy™ of MongoDB, available to all customers in the US-West-1 data center. This technology makes it easy to deploy either a development or production MongoDB replica set on GoGrid’s high-performance infrastructure. GoGrid’s 1-Button Deploy™ technology combines the capabilities of one of the leading NoSQL databases with our expertise in building high-performance Cloud Servers.

MongoDB is a scalable, high-performance, open source, structured storage system. MongoDB provides JSON-style document-oriented storage with full index support, sharding, sophisticated replication, and compatibility with the MapReduce paradigm. MongoDB focuses on flexibility, power, speed, and ease of use. GoGrid’s 1-Button Deploy™ of MongoDB takes advantage of our SSD Cloud Servers while making it easy to deploy a fully configured replica set.

Why GoGrid Cloud Servers?

SSD Cloud Servers have several high-performance characteristics. They all come with attached SSD storage and large available RAM for the high I/O uses common to MongoDB. MongoDB will attempt to place its working set in memory, so the ability to deploy servers with large available RAM is important. Plus, whenever MongoDB has to write to disk, SSDs provide for a more graceful transition from memory to disk. SSD Cloud Servers use a redundant 10-Gbps public and private network to ensure you have the maximum bandwidth to transfer your data. You can use can GoGrid’s 1-Button Deploy™ to provision either a 3-server development replica set or a 5-server production replica set with Firewall Service enabled.

Development Environments

The smallest recommended size for a development replica set is 3 servers. Although it’s possible to run MongoDB on a single server, you won’t be able to test failover or how a replica set behaves in production. You’ll most likely have a small working set so you won’t need as much RAM, but will still benefit from SSD storage and a fast network.

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How to Deploy a Riak Cluster in 5 Minutes on GoGrid

Friday, January 31st, 2014 by

The first big challenge to overcome with any new NoSQL database deployment is figuring out how to deploy the cluster in an environment that lets you scale as needed within a single data center and even across multiple data centers. To save cash, many customers make the mistake of trialing the product on cheap hardware with limited RAM across clusters that are inadequate for the application.

We think there’s a better way to run your evaluation. At GoGrid, we’ve made it possible to deploy a 5-node Riak cluster on beefy, high-performance machines with the click of a button. Check out the specs we’re providing as an orchestrated deployment using our 1-Button Deploy™ technology:

  • 5 nodes
  • 16 GB RAM per node
  • 16 cores per node
  • 640 GB storage per node
  • 10-Gbps network
  • 40-Gbps private network connectivity to additional Block Storage volumes (as needed)

Once the first cluster is deployed, you can point-and-click to add more nodes as you need them. Geek out for a moment on what you can do with this technology: You can run a user/session store for your application, use it to target and serve advertising, perform MapReduce operations, or any number of other things with just a few clicks of the mouse. And you can do it all in 4 easy steps.

Step 1: Login to GoGrid

To get started, login to your GoGrid account at https://my.gogrid.com to access the management console. If you don’t yet have an account, go ahead and create one: visit www.gogrid.com and click the Get Started button in the upper right-hand corner of the screen.

Step 2: Add New Infrastructure

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5 Ways Big Data Can Improve Your Business in 2014

Wednesday, January 29th, 2014 by

The concept of Big Data escapes many, but those who take the time to understand and use it benefit significantly. It’s predicted that Big Data will become huge in 2014, but companies that make business intelligence solutions a priority early in January will undoubtedly gain an edge over their competition. From data-based decisions to improving customer satisfaction, here are 5 ways Big Data can improve your business in 2014.

How big data will change your business in 2014

How Big Data will change your business in 2014

1. Access trends through social media
Big Data and the analytics that decipher it can easily zero in on a particular trend in social media and capitalize on it in ways that are advantageous to your business. Quobole uses the example of a location-based trend. That means a business can detect when a store is getting a notable amount of buzz on social media through unstructured data. Using that information, the business’s marketing team can then send out a blast on social media encouraging users to visit the store and give them an incentive to make a purchase. That’s just one example of capitalizing on social media trends with Big Data.

2. Rely less on gut feelings
In the past, many business decisions have been made based solely on instinct. Increasingly, however, companies are relying on data collected through market research or online trends. Big Data gives companies even more information to go on, enabling them to make business decisions that are more factually based and considerably less risky. If you have actual data, you can weigh real-life pros and cons before plunging into the deep end.

3. Stay ahead of the competition
Because Big Data is expected to go mainstream in the next year, businesses can get a head start on the competition by familiarizing themselves with business intelligence solutions. The sooner businesses start to use trends found by unstructured data, the larger head start they’ll have on the competition. It’s strategies like this that can turn underdog companies into market leaders and keep these top businesses at the forefront of their industry.

4. Make customers more satisfied
One of the biggest ways Big Data is changing businesses is by improving customer service. According to The Wall Street Journal, Netflix began using unstructured data for this purpose in 2008. After an outage, the company used the data to spot problem areas and improve the technology. It also used the data to inform the future viewing suggestions they offer customers. Big Data lets Netflix know where the most traffic is on their website and helps on-site engineers plan for better network capacity. Now, Netflix is a top company for on-demand Internet streaming.

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Big Data Cloud Servers for Hadoop

Monday, January 13th, 2014 by

GoGrid just launched Raw Disk Cloud Servers, the perfect choice for your Hadoop data node. These purpose-built Cloud Servers run on a redundant 10-Gbps network fabric on the latest Intel Ivy Bridge processors. What sets these servers apart, however, is the massive amount of raw storage in JBOD (Just  a Bunch of Disks) configuration. You can deploy up to 45 x 4 TB SAS disks on 1 Cloud Server.

These servers are designed to serve as Hadoop data nodes, which are typically deployed in a JBOD configuration. This setup maximizes available storage space on the server and also aids in performance. There are roughly 2 cores allocated per spindle, giving these servers additional MapReduce processing power. In addition, these disks aren’t a virtual allocation from a larger device. Each volume is actually a dedicated, physical 4 TB hard drive, so you get the full drive per volume with no initial write penalty.

Hadoop in the cloud

Most Hadoop distributions call for a name node supporting several data nodes. GoGrid offers a variety of SSD Cloud Servers that would be perfect for the Hadoop name node. Because they are also on the same 10-Gbps high-performance fabric as the Raw Disk Cloud Servers, SSD servers provide low latency private connectivity to your data nodes. I recommend using at least the X-Large SSD Cloud Server (16 GB RAM), although you may need a larger server, depending on the size of your Hadoop cluster. Because Hadoop stores metadata in memory, you’ll want more RAM if you have a lot of files to process. You can use any size Raw Disk Cloud Server, but you’ll want to deploy at least 3. Also, each Raw Disk Cloud Server has a different allocation of raw disks, which are illustrated in the table below. The Cloud Server in the illustration is the smallest size that has multiple disks per Cloud Server. Hadoop defaults to a replication factor of three, so to protect your data from failure, you’ll want to have at least 3 data nodes to distribute data. Although Hadoop attempts to replica data to different racks, there’s no guarantee that your Cloud Servers will be on different racks.

Note that the example below is for illustrative purposes only and is not representative of a typical Hadoop cluster; for example, most Cloudera and Hortonworks sizing guides start at 8 nodes. These configurations can differ greatly depending on if you intend to use the cluster for development, production, or production with HBase added. This includes the RAM and disk sizes (less of both for development, most likely more for HBase). Plus, if you’re thinking of using these nodes for production, you should consider adding a second name node.

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