Disney And Its Big Data Plan Is Home Built
January 29, 2013
When most companies aim to take advantage of big data, usually they turn to a commercial company to set them up with a deployment plan and software. Disney, one of the world’s biggest companies, decided to build its own big data initiative in-house and with open source software. Gigaom has all of the details on the Mouse’s plans in the article, “How Disney Built A Big Data Platform On A Startup Budget.” When Arun Jacob, Disney’s director of data solutions, was told to build a big data platform, he knew he needed to make something that would be useful to the entire corporation.
Disney’s platform uses MongoDB, Hadoop, and Cassandra, but while Jacob tried to use as much open source software as possible he did tap into Disney’s large purse and buy commercial software. The project is moving along well, but Jacob had this to say:
“Still, after all the work he put into building Disney’s big data platform, it’s not exactly a process Jacob is hoping to repeat as the platform evolves. The tools for managing big data are getting better, he said, so he still does a build-versus-buy analysis when it’s time to make a change. Building custom tools is fine when you don’t have a choice, but it’s not always wise when buying something could save untold man-hours and headaches.”
Economy is good. Now why does Disney charge thousands for a mouse guide who takes well-heeled customers through the exits to skip the serpentine lines. Oh, to create money to do big data economically. M I C K E Y, see you real soon.
Whitney Grace, January 29, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
PolySpot Enables Information Access for Analysts and Business Management
January 28, 2013
The decline in the pricing of RAM and the popularity of cloud computing in conjunction with the need for faster queries has produced a multitude of options for enterprise organizations to increase productivity and efficiency. O’Reilly Radar discusses the demand for technology and tools that facilitate interactive query performance. The article “Need Speed for Big Data? Think In-Memory Data Management” explains how these tools lead to real-time communication and reports.
The article informs us about interactive query performance:
Faster query response times translate to more engaged and productive analysts, and real-time reports. Over the past two years several in-memory solutions emerged to deliver 5X-100X faster response times. A recent paper from Microsoft Research noted that even in this era of big data and Hadoop, many MapReduce jobs fit in the memory of a single server. To scale to extremely large datasets several new systems use a combination of distributed computing (in-memory grids), compression, and (columnar) storage technologies.
We have seen an increase in the amount of technologies available to address engagement and productivity issues in the workplace, but there are none that we have seen to match the user experience and infrastructure technology of PolySpot. This solution enables information access while maintaining data integrity and adding semantic enrichment. What more could an analyst or a decision-maker want?
Megan Feil, January 28, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search.
PolySpot Disseminates Big Data Gold
January 25, 2013
Even though many companies started researching big data initiatives for their organization, they did not actively pursue the technologies or the workforce needed to turn their data into gold. Experts in the field are opining in their predictions that 2013 will be the year that big data really hits and companies utilizing it will have a competitive advantage against others who are behind the curve. GigaOM reports on an opportunity for professionals interested in big data in the brief write-up, “Meet Big Data Bigwigs at Structure: Data.”
The opportunity for networking and learning from industry experts will be from March 20-12 and is called Structure:Data. The article tells us more:
‘Whether we know it or not, data — big, small or otherwise — is becoming a central component to the way we live our lives,’ says GigaOM writer Derrick Harris in his big data predictions for 2013. At Structure:Data we’ll delve into what lies ahead for big data, as we explore the technical and business opportunities that the growth of big data has created. Topics include case studies of big data implementations, the future of Hadoop, machine learning, the looming data-scientist crisis and the top trends in big data technologies.
There are plenty of insights and opportunities to be mined from big data and there are some firms that are already tapping into big data. Tools like PolySpot make this an easy feat for small businesses to large corporations with their scalable solutions to disseminate insights from terabytes in real time across the enterprise.
Megan Feil, January 25, 2012
Sponsored by ArnoldIT.com, developer of Beyond Search
Apache Lucene Solr Updates
January 25, 2013
The DZone Big Data/BI Zone has let us know that a new version of Apache Lucene Solr has hit the internet. Apache Lucene Solr 3.6.2 has been unveiled, and it will roll into many other products that build upon the open source code. Read the details in, “Apache Lucene Solr 3.6.2.”
The gist of the release is in the first few lines:
“Apache Lucene and Solr PMC recently announced another version of Apache Lucene library and Apache Solr search server numbred 3.6.2. This is a minor bugfix release concentrated mainly on bugfixes in Apache Lucene library.
Apache Lucene 3.6.2 library can be downloaded from the following address: http://lucene.apache.org/core/mirrors-core-3x-redir.html?. Apache Solr 3.6.2 can be downloaded at the following URL address: http://lucene.apache.org/solr/mirrors-solr-3x-redir.html?”
Two products sure to be affected and improved by the update are LucidWorks Search and LucidWorks Big Data. LucidWorks chooses to use Lucene Solr as its foundation because of its dependability, agility, and strong developer and user communities. LucidWorks and any product that builds on open source and is going to be strong, secure, and continuously updated, just by its nature, and therefore a better choice than a proprietary option.
Emily Rae Aldridge, January 25, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Datastax Announces Next Enterprise Version
January 24, 2013
Datastax, a company built around the Cassandra NoSQL database, is releasing Datastax Enterprise 3.0. SysCon Media offers the full release announcement in, “DataStax Enterprise (DSE) 3.0 Offers Most Comprehensive Security Feature Set Among All NoSQL Providers; Enables Enterprises to Adopt NoSQL Databases While Safely Scaling Their Big Data Infrastructure.”
The article begins:
“DataStax, the company that powers the big data apps that transform business, today announced the early adopter program (EAP) launch of DataStax Enterprise (DSE) 3.0. The new version provides core security capabilities to the entire Cassandra community, as well as the advanced data protection that businesses expect in an enterprise-grade database. DSE 3.0 supplies the type of security framework that allows modern enterprises to confidently adopt NoSQL databases as they safely scale their big data infrastructure.”
Datastax makes a good product, but it is by no means the only option for managing Big Data in the enterprise. And as far as security is concerned, other software solutions do a good job as well. One option that combines security with Big Data usability is LucidWorks and their LucidWorks Big Data product. LucidWorks is built on Apache Lucene, so it is a completely different animal, but the reviews are good and everyone agrees it is a dependable option for getting the most out of your Big Data.
Emily Rae Aldridge, January 24, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Faster Decisions Made Using Information Delivery from PolySpot
January 23, 2013
The amount of data a company has in its possession means nothing unless the company has the tools and team to extract information from the sheer numbers and data bits. CIO recently revealed an article called, “How To Use Big Data to Make Faster and Better Business Decisions.”
Important business related questions requiring action can be answered and assessed in days rather than months. With such potential on the table for big data, NewVantage Partners conducted a study to determine how organizations are using big data. It turns out that 85% of their respondents reported big data initiatives as currently underway.
The article states:
Respondents gave a number of reasons for their investments in Big Data, from reducing risk to creating higher-quality products and services. But two reasons were clear leaders: achieving better, fact-based decision-making and improving the customer experience. Of course, these are leading reasons for investments in traditional business intelligence (BI) analytics, too.
Emphasis rests on the amount of time it takes for companies to answer the questions they need answered. Luckily, there are technologies such as PolySpot that enable information access across the enterprise. Communication and analysis can thus take place in near real-time.
Megan Feil, January 23, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Connectors Allow for Comprehensive Enterprise Information Delivery
January 22, 2013
Countless studies have shown that while the large majority of companies see great value in big data, they have not deployed the technologies that are poised to help them begin to collect, store and analyze big data. Information Week reports on Information Builders chief markting officer Michael Corcoran and his participation as a panelist at a Gartner conference in “Big Data Master Plan: Time To Start.”
Corcoran found that many audience members were not sure about if they were going to purchase technologies to transform big data into meaningful opportunities because they were not sure of the definition of big data and the power it holds.
After detailing the basics, he discusses some of the challenges enterprise organizations face:
One snag that organizations often encounter when setting up a big data initiative is finding ways to ensure that unstructured information from multiple sources is accurate and clean, and that it integrates well with existing data systems. “When they start to think about some of the new opportunities for big data, including social media or third-party industry data, how do they marry that elegantly?” Corcoran asked rhetorically.
Many organizations have found success in big data technologies utilizing connectors that allow users to work with data from multiple apps and information sources – structured and unstructured. These technologies enable true enterprise information delivery.
Megan Feil, January 22, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
PolySpot Enables Access to Actionable Insights
January 21, 2013
After several years of articles focused simply on what big data means, the time has finally arrived where many media outlets are moving beyond definitions in their coverage. HR Bartender breaches the subject of massive volumes of petabytes in regards to the opportunities and actionable information it produces in their recent article, “Moving from Big Data to Real Insight.”
The article tells us to acknowledge but bypass skepticism, focus on success and build off of small victories. Among many professional tips and guidelines for creating insights out of numbers, the author emphasizes the prime motivation as enabling a better customer and client experience.
The article recommends:
It’s important to understand how to get insights from our data. And before companies try to incorporate big data into their strategy, here are a few things to consider. Identify the “why”. Companies need to know why they are gathering data. Example: In the IBM CEO study, chief executives talk about building data to serve their customers. Their goal is to empower customer facing staff by using analytics to create a better customer experience.
Moving the needle from a chaotic array of data holed up in silos in various programs and applications will be challenging without the proper infrastructure component. PolySpot, for example, with over one hundred connectors aids in the technological side of information access.
Megan Feil, January 21, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Strata Conference Focuses on Big Data
January 21, 2013
Big Data is going to be the focus of 2013, particularly when it comes to open source innovation. O’Reilly Strata Conference 2013 is devoted to Big Data and pressing complimentary issues like: enterprise IT, design, Hadoop, open source and law, and applications. Read more at the official conference promotion site, “Tap into the Collective Intelligence of the Best Minds in Data.”
The conference promises the following:
“The future belongs to those who understand how to collect and use their data successfully. And that future happens at Strata. The breadth and depth of expertise at Strata is unsurpassed—with over 120 speakers and 100 presentations and events, you’ll find solutions to your most pressing data issues. The conference program covers strategy, technology, and policy.”
The conference will take place February 26 – 28, 2013 in Santa Clara, California. Register now for the early discount. For those who cannot attend, still check out the options to connect with the community via the website. Also, for those who are interested in the best Big Data solution for their organization’s enterprise, a deeper look into LucidWorks Big Data may be in order. It is leading the field in Big Data for enterprise, standing firmly on the trusted name of LucidWorks, a leader in open source for enterprise for years.
Emily Rae Aldridge, January 21, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Indiana University and a Big Data Set
January 20, 2013
Short honk: If you are looking for a big data set to show off your Big Data system, Indiana University can help. “Click Dataset” says:
To foster the study of the structure and dynamics of Web traffic networks, we make available a large dataset (‘Click Dataset’) of HTTP requests made by users at Indiana University. Gathering anonymized requests directly from the network rather than relying on server logs and browser instrumentation allows one to examine large volumes of traffic data while minimizing biases associated with other data sources.
There are some caveats, but for the firms with sci-fi type Big Data analytics’ systems, the issues should be irrelevant. “Truthy” in advertising? For companies with real world systems, the caveats are important.
Stephen E Arnold, January 20, 2013
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