The Hortonworks Blog

Posts categorized by : Big Data

A few weeks back we posted a definition of “big data”.  There was definitely some internal conversation about the term and if this definition had captured what the term means.  Sum finding: it is a loaded term.  It means a lot of different things to a lot of different people.

When I first joined Hortonworks, I bought in to the three V’s (volume velocity and variety) definition of big data. …

As a preview to the April 30th webinar: Hadoop & the EDW: When to Use Which, Chad Meley, Global Director of Marketing at Teradata, interviewed the two luminary speakers, Eric Baldeschwieler (aka “eric14”) and Stephen Brobst, about the purpose of their presentation and what you can expect to take away from their shared experiences.

Chad:  “Eric, in this webinar you’re going to talk about the strategic role of relational big data technologies, which have come under fire in some circles with the rise of Hadoop. …

In a recent blog post I mentioned the 4 reasons for using Hadoop for data science. In this blog post I would like to dive deeper into the last of these reasons: data agility.

In most existing data architectures, based on relational database systems, the data schema is of central importance, and needs to be designed and maintained carefully over the lifetime of the project. Furthermore, whatever data fits into the schema will be stored, and everything else typically gets ignored and lost.…

Data scientists are in high demand these days. Everyone seems to be hiring a team of data scientists, yet many are still not quite sure what data science is all about, and what skill set they need to look for in a data scientist to build a stellar Hadoop data science team. We at Hortonworks believe data science is an evolving discipline that will continue to grow in demand in the coming years, especially with the growth of Hadoop adoption.…

While we are quite a far way away from hearing “Houston, tranquility base here… the eagle has landed”, the HP moonshot is definitely pushing us all toward a new class of infrastructure to run more efficient workloads, like Apache Hadoop. Hortonworks applauds the development of flexible Big Data appliances like Moonshot. We are excited about this development as it signals alignment across development, operations and infrastructure within organizations.  For quite some time, our team has been accustomed to a natural balance required across these three constituents and now the server the market is joining in on the game.…

Over the last 10 years or so, large web companies such as Google, Yahoo!, Amazon and Facebook have successfully applied large scale machine learning algorithms over big data sets, creating innovative data products such as online advertising systems and recommendation engines.

Apache Hadoop is quickly becoming a central store for big data in the enterprise, and thus is a natural platform with which enterprise IT can now apply data science to a variety of business problems such as product recommendation, fraud detection, and sentiment analysis.…

‘Big Data’ has become a hot buzzword, but a poorly defined one. Here we will define it.

Wikipedia defines Big Data in terms of the problems posed by the awkwardness of legacy tools in supporting massive datasets:

In information technology, big data[1][2] is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

It is better to define ‘Big Data’ in terms of opportunity, in terms of transformative economics.…

Jaspersoft, a Hortonworks certified technology partner, recently completed a survey on the early use of Apache Hadoop in the enterprise. The company found 38% of respondents require real-time or near real-time analytics for their Big Data with Hadoop. Also, within the enterprise, there is a diverse group of people who use Hadoop for such insights: 63% are application developers, 15% are BI report developers and 10% are BI admins or casual business users.…

Please join Hortonworks, Impetus and Entravision/Luminar for a webinar on how big data analytics is being used in the advertising industry to identify predictability models of consumer behavior. The webinar will take place on Tuesday, February 12th at 1pm (EST), 10am (PST).

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Big data analytics is becoming increasingly useful to professionals in digital media, gaming, healthcare, security, finance and government, and nearly every industry you can name. Companies are analyzing vast amounts of data from various sources to shed light on customer behaviors, accelerate lead conversion, pinpoint security threats and enrich social media marketing efforts.…

Please join Hortonworks and Appnovation for a webinar titled “Bigger Data on Your Budget” taking place on Wednesday, February 13th at 2pm EST, 11am PST.

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Appnovation is a new Hortonworks Systems Integrator partner that is focused on cutting edge open source technologies. They are experts in Drupal, Alfresco, SproutCore and now Apache Hadoop.

In advance of this webinar, I interviewed Dave Porter, Appnovation & SproutCore Lead Developer, about the technologies they support and how Appnovation and Hortonworks are working together to provide big insights without breaking the bank.…

The customer data that companies collect from websites, social media, blogs, digital advertising and mobile is exploding. And as big data gets bigger, the amount of untapped insights available from analyzing that day is also growing exponentially. Marketers covet those insights as a way to better understand and engage with their customers and ultimately drive revenue—but how do they get to it?

According to Gartner, organization that successfully integrate high-value, diverse new information types and sources into a coherent information management infrastructure will outperform their industry peers financially by more than 20 percent.* Fortunately, a new solution that combines Hortonworks Data Platform (HDP) with the expertise of eSage Group allows marketing professionals to extract value from Big Data, quickly and with relative ease.…

If Pig is the “duct tape for big data“, then DataFu is the WD-40. Or something.

No, seriously, DataFu is a collection of Pig UDFs for data analysis on Hadoop. DataFu includes routines for common statistics tasks (e.g., median, variance), PageRank, set operations, and bag operations.

It’s helpful to understand the history of the library. Over the years, we developed several routines that were used across LinkedIn and were thrown together into an internal package we affectionately called “littlepiggy.” The unfortunate part, and this is true of many such efforts, is that the UDFs were ill-documented, ill-organized, and easily got broken when someone made a change.…

Introduction

This is part three of a Big Data Security blog series. You can read the previous two posts here: Part One / Part Two.

When Russell Jurney and I first teamed up to write these posts we wanted to do something that no one had done before to demonstrate the power of Big Data, the simplicity of Pig and the kind of Big Data Security Analytics we perform at Packetloop.…

The Hortonworks Data Platform (HDP) conveniently integrates numerous Big Data tools in the Hadoop ecosystem. As such, it provides cluster-oriented storage, processing, monitoring, and data integration services. HDP simplifies the deployment and management of a production Hadoop-based system.

In Hadoop, data is represented as key/value pairs. In HBase, data is represented as a collection of wide rows. These atomic structures makes global data processing (via MapReduce) and row-specific reading/writing (via HBase) simple.…

For the last couple months, Hortonworks has been excited to be a proud sponsor of the Big Analytics 2012 roadshow.  These roadshows have provided us some great insights into the role of Apache Hadoop in this emerging Big Data market.  We had some great discussions with attendees regarding their current and future plans for the use of Hadoop and other Big Data technologies. Another interesting insight was the need for Data skills, people who know what to ask of that data and how to use tools like Hadoop to provide patterns, answers, interpretations and present the data.…

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