Tag: analysis

Jaspersoft 4.1 launched

http://www.jaspersoft.com/events/jaspersoft-41-webinar-north-america

one more webinar, but a newer software and a changing paradigm.

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Webinar: Introducing Jaspersoft 4.1- North America

 Date: June 8, 2011

Time: 10:00 AM PT/1:00 PM ET
Duration: 60 Minutes
Language: English

Self-service Business Intelligence helps individuals and organizations respond quickly to operational and strategic decisions.  A driving factor for the success of self-service BI is an intuitive and integrated UI that spans reporting, dashboards, and data analysis. Additionally, the rise of the cloud and big-data environments presents new opportunities for organizations that can analyze and respond to these emerging data sources.

In this webinar, see how the new Jaspersoft Business Intelligence Suite 4.1 release achieves all this and more.
Register now and learn how you can now take advantage of:

  • Modern self-service BI for reporting and analysis: powerful, unified capabilities for both ad hoc reporting and analysis tasks.
  • Flexible insight into any data source: a seamless analytics UI for both data stored within relational, OLAP, and big data stores.
  • Maximum performance—now designed to take advantage of 64-bit processors.

    Join the webinar and explore the world’s most advanced and affordable BI suite through live demos, interactive Q&A and more.

the upcoming Jaspersoft 4.1 Webinar and Demo. Here’s a preview of what you’ll see:

  • Unified drag-and-drop UI for reporting and analytics. Jaspersoft 4.1 delivers powerful, unified drag-and-drop usability to both ad hoc reporting and analysis tasks while supporting both in-memory and OLAP engines. That means easier, more powerful analysis for business users and a faster route to self-service BI.
  • Insight against any data source. The analytics UI provides easier, more powerful analysis across relational, OLAP, and Big Data stores.
  • High performance with native 64-bit installer support. With Jaspersoft 4.1, you can also scale BI applications to new performance heights, thanks to full support for today’s powerful 64-bit processors.

Join us for the webinar and see how quickly and easily BI Builders like you can deliver true, self-service BI, combining reports, dashboards, and analytics, against virtually any data source — all through a single, web-based UI.

Related articles

Who writes white papers?

A social network diagram
Image via Wikipedia

There are four main types of commercial white papers:

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.
Name the best white paper you ever read? (comment that in the field)..
What categoy of white papers is the best?
Do you think white papers are too expensive or they give adequate ROI?
To be continued- including

  1. demographic and social network analysis of analysts and white paper sponsors to measure interaction effects.
  2. white papers segmented by type of software company
  3. proc freq analysis of the words frequency data viz in white papers written by same analysts for different companies on same topics.
  4. Race and ethnic analysis of influencers and analysts in Business Analysts and Business Intelligence. – Null hypothesis – it is not a white mans world, women, Hispanics and other minorities are adequately represented.
Why I am doing this?
I am writing a white paper on WHO writes a white paper? 
Sponsorships are invited- but academics and startups in analytics may be preferred.
Related articles

East loves Gold and USD. and chokes on it

A brief analysis shows how Eastern Hemisphere loves gold and USD so much

I did the graph in JMP since it is an easier GUI for me to use (I do have some learning disabilities).

https://www.cia.gov/library/publications/the-world-factbook/rankorder/2188rank.html

RANK
 COUNTRY RESERVES OF FOREIGN EXCHANGE AND GOLD DATE OF INFORMATION
1 China
$ 2,622,000,000,000
31 December 2010 est.
2 Japan
$ 1,096,000,000,000
31 December 2010 est.
3 Russia
$ 483,100,000,000
30 November 2010
4 Saudi Arabia
$ 456,200,000,000
31 December 2010 est.
5 Taiwan
$ 387,200,000,000
31 December 2010 est.
6 Brazil
$ 290,900,000,000
31 December 2010 est.
7 India
$ 284,100,000,000
31 December 2010 est.
8 Korea, South
$ 274,600,000,000
31 December 2010 est.
9 Hong Kong
$ 268,900,000,000
31 December 2010 est.
10 Switzerland
$ 236,600,000,000
31 December 2010
11 Singapore
$ 225,800,000,000
31 December 2010 est.
12 Thailand
$ 176,100,000,000
31 December 2010 est.
13 Algeria
$ 150,100,000,000
31 December 2010 est.
14 Mexico
$ 116,400,000,000
31 December 2010 est.
15 Libya
$ 107,300,000,000
31 December 2010 est.
16 Malaysia
$ 106,500,000,000
31 December 2010 est.
17 Poland
$ 99,760,000,000
31 December 2010 est.
18 Indonesia
$ 96,210,000,000
31 December 2010 est.
19 Turkey
$ 78,000,000,000
31 December 2010 est.
20 Iran
$ 75,060,000,000
31 December 2010 est.
21 Israel
$ 66,980,000,000
31 December 2010 est.
22 Philippines
$ 62,370,000,000
31 December 2010 est.
23 Argentina
$ 53,610,000,000
31 December 2010 est.
24 Romania
$ 50,510,000,000
31 December 2010 est.
25 Iraq
$ 45,680,000,000
31 December 2010 est.
26 South Africa
$ 45,520,000,000
31 December 2010 est.
27 Hungary
$ 44,990,000,000
31 December 2010 est.
28 Peru
$ 44,110,000,000
31 December 2010
29 Nigeria
$ 43,360,000,000
31 December 2010 est.
30 Czech Republic
$ 42,340,000,000
31 December 2010 est.
31 Lebanon
$ 41,570,000,000
31 December 2010 est.
32 United Arab Emirates
$ 39,100,000,000
31 December 2010 est.
33 Australia
$ 38,620,000,000
31 December 2010 est.
34 Egypt
$ 35,720,000,000
31 December 2010 est.
35 Ukraine
$ 32,910,000,000
31 December 2010 est.
36 Kazakhstan
$ 32,440,000,000
31 December 2010 est.
37 Venezuela
$ 29,490,000,000
31 December 2010 est.
38 Colombia
$ 28,500,000,000
31 December 2010 est.
39 Chile
$ 26,080,000,000
31 December 2010 est.
40 Morocco
$ 24,570,000,000
31 December 2010 est.
41 Macau
$ 23,730,000,000
42 Kuwait
$ 22,420,000,000
31 December 2010 est.
43 Qatar
$ 22,410,000,000
31 December 2010 est.
44 Austria
$ 21,890,000,000
31 December 2010 est.
45 Syria
$ 17,960,000,000
31 December 2010 est.
46 New Zealand
$ 17,850,000,000
31 December 2010 est.
47 Bulgaria
$ 17,270,000,000
31 December 2010 est.
48 Angola
$ 16,890,000,000
31 December 2010 est.
49 Pakistan
$ 16,100,000,000
31 December 2010 est.
50 Serbia
$ 15,100,000,000
30 November 2010 est.
51 Oman
$ 14,000,000,000
31 December 2010 est.
52 Croatia
$ 13,790,000,000
31 December 2010 est.
53 Vietnam
$ 13,000,000,000
31 December 2010 est.
54 Jordan
$ 12,640,000,000
31 December 2010 est.
55 Tunisia
$ 11,230,000,000
31 December 2010 est.
56 Turkmenistan
$ 10,810,000,000
31 December 2010 est.
57 Bangladesh
$ 10,790,000,000
31 December 2010 est.
58 Uzbekistan
$ 10,500,000,000
31 December 2010 est.
59 Bolivia
$ 9,730,000,000
31 December 2010 est.
60 Trinidad and Tobago
$ 9,659,000,000
31 December 2010 est.
61 Finland
$ 9,128,000,000
31 December 2010 est.
62 Botswana
$ 7,834,000,000
31 December 2010 est.
63 Uruguay
$ 7,700,000,000
31 December 2010 est.
64 Latvia
$ 7,170,000,000
31 December 2010 est.
65 Lithuania
$ 6,418,000,000
31 December 2010 est.
66 Azerbaijan
$ 6,330,000,000
31 December 2010 est.
67 Belarus
$ 5,755,000,000
31 December 2010 est.
68 Yemen
$ 5,744,000,000
31 December 2010 est.
69 Guatemala
$ 5,709,000,000
31 December 2010 est.
70 Sri Lanka
$ 5,630,000,000
31 December 2010 est.
71 Cuba
$ 4,847,000,000
31 December 2010 est.
72 Kenya
$ 4,585,000,000
31 December 2010 est.
73 Costa Rica
$ 4,584,000,000
31 December 2010 est.
74 Iceland
$ 4,206,000,000
31 December 2010 est.
75 Bosnia and Herzegovina
$ 4,200,000,000
31 December 2010 est.
76 Paraguay
$ 4,130,000,000
31 December 2010 est.
77 Congo, Republic of the
$ 4,123,000,000
31 December 2010 est.
78 Equatorial Guinea
$ 4,086,000,000
31 December 2010 est.
79 Cameroon
$ 4,023,000,000
31 December 2010 est.
80 Cote d’Ivoire
$ 3,985,000,000
31 December 2010 est.
81 Cambodia
$ 3,840,000,000
31 December 2010 est.
82 Ghana
$ 3,800,000,000
31 December 2010 est.
83 Bahrain
$ 3,766,000,000
31 December 2010 est.
84 Burma
$ 3,762,000,000
31 December 2010 est.
85 Uganda
$ 3,743,000,000
31 December 2010 est.
86 Tanzania
$ 3,687,000,000
31 December 2010 est.
87 Estonia
$ 3,641,000,000
31 December 2010 est.
88 Ecuador
$ 3,590,000,000
31 December 2010 est.
89 Panama
$ 3,525,000,000
31 December 2010 est.
90 Papua New Guinea
$ 3,017,000,000
31 December 2010 est.
91 El Salvador
$ 2,882,000,000
31 December 2010 est.
92 Dominican Republic
$ 2,705,000,000
31 December 2010 est.
93 Gabon
$ 2,602,000,000
31 December 2010 est.
94 Mauritius
$ 2,360,000,000
31 December 2010 est.
95 Georgia
$ 2,350,000,000
31 December 2010 est.
96 Honduras
$ 2,302,000,000
31 December 2010 est.
97 Zambia
$ 2,287,000,000
31 December 2010 est.
98 Armenia
$ 2,247,000,000
31 December 2010 est.
99 Macedonia
$ 2,217,000,000
30 November 2010 est.
100 Senegal
$ 2,200,000,000
31 December 2010 est.
101 Ireland
$ 2,104,000,000
31 December 2010
102 Sudan
$ 2,063,000,000
31 December 2010 est.
103 Albania
$ 1,992,000,000
31 December 2010 est.
104 Mozambique
$ 1,982,000,000
31 December 2010 est.
105 Namibia
$ 1,961,000,000
31 December 2010 est.
106 Ethiopia
$ 1,880,000,000
31 December 2010 est.
107 Jamaica
$ 1,850,000,000
31 December 2010 est.
108 Moldova
$ 1,710,000,000
31 December 2010 est.
109 Kyrgyzstan
$ 1,615,000,000
31 December 2010 est.
110 Burkina Faso
$ 1,588,000,000
31 December 2010 est.
111 Haiti
$ 1,587,000,000
31 December 2010 est.
112 Nicaragua
$ 1,580,000,000
31 December 2010 est.
113 Benin
$ 1,254,000,000
31 December 2010 est.
114 Slovakia
$ 1,160,000,000
31 January 2010 est.
115 Madagascar
$ 1,038,000,000
31 December 2010 est.
116 Congo, Democratic Republic of the
$ 1,010,000,000
March 2010 est.
117 Lesotho
$ 893,000,000
31 December 2010 est.
118 Chad
$ 868,000,000
31 December 2010 est.
119 Rwanda
$ 816,000,000
31 December 2010 est.
120 Laos
$ 756,000,000
31 December 2010 est.
121 Swaziland
$ 708,000,000
31 December 2010 est.
122 Togo
$ 686,000,000
31 December 2010 est.
123 Barbados
$ 620,000,000
2007
124 Malta
$ 522,000,000
31 December 2010 est.
125 Guyana
$ 506,000,000
31 December 2010 est.
126 Zimbabwe
$ 376,000,000
31 December 2010 est.
127 Burundi
$ 320,000,000
31 December 2010 est.
128 Tajikistan
$ 303,000,000
31 December 2010 est.
129 Malawi
$ 301,000,000
31 December 2010 est.
130 Cape Verde
$ 296,000,000
31 December 2010 est.
131 Suriname
$ 263,300,000
2006
132 Belize
$ 219,000,000
31 December 2010 est.
133 Gambia, The
$ 203,000,000
31 December 2010 est.
134 Seychelles
$ 193,000,000
31 December 2010 est.
135 Eritrea
$ 104,000,000
31 December 2010 est.
136 Samoa
$ 70,150,000
FY03/04
137 Sao Tome and Principe
$ 46,000,000
31 December 2010 est.
138 Tonga
$ 40,830,000
FY04/05
139 Vanuatu
$ 40,540,000
2003

AsterData still alive;/launches SQL-MapReduce Developer Portal

so apparantly ole client AsterData continues to thrive under gentle touch of Terrific Data

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Aster Data today launched the SQL-MapReduce Developer Portal, a new online community for data scientists and analytic developers. For your convenience, I copied the release below and it can also be found here. Please let me know if you have any questions or if there is anything else I can help you with.

Sara Korolevich

Point Communications Group for Aster Data

sarak@pointcgroup.com

Office: 602.279.1137

Mobile: 623.326.0881

Teradata Accelerates Big Data Analytics with First Collaborative Community for SQL-MapReduce®

New online community for data scientists and analytic developers enables development and sharing of powerful MapReduce analytics


San Carlos, California – Teradata Corporation (NYSE:TDC) today announced the launch of the Aster Data SQL-MapReduce® Developer Portal. This portal is the first collaborative online developer community for SQL-MapReduce analytics, an emerging framework for processing non-relational data and ultra-fast analytics.

“Aster Data continues to deliver on its unique vision for powerful analytics with a rich set of tools to make development of those analytics quick and easy,” said Tasso Argyros, vice president of Aster Data Marketing and Product Management, Teradata Corporation. “This new developer portal builds on Aster Data’s continuing SQL-MapReduce innovation, leveraging the flexibility and power of SQL-MapReduce for analytics that were previously impossible or impractical.”

The developer portal showcases the power and flexibility of Aster Data’s SQL-MapReduce – which uniquely combines standard SQL with the popular MapReduce distributed computing technology for processing big data – by providing a collaborative community for sharing SQL-MapReduce expert insights in addition to sharing SQL-MapReduce analytic functions and sample code. Data scientists, quantitative analysts, and developers can now leverage the experience, knowledge, and best practices of a community of experts to easily harness the power of SQL-MapReduce for big data analytics.

A recent report from IDC Research, “Taking Care of Your Quants: Focusing Data Warehousing Resources on Quantitative Analysts Matters,” has shown that by enabling data scientists with the tools to harness emerging types and sources of data, companies create significant competitive advantage and become leaders in their respective industry.

“The biggest positive differences among leaders and the rest come from the introduction of new types of data,” says Dan Vesset, program vice president, Business Analytics Solutions, IDC Research. “This may include either new transactional data sources or new external data feeds of transactional or multi-structured interactional data — the latter may include click stream or other data that is a by-product of social networking.”

Vesset goes on to say, “Aster Data provides a comprehensive platform for analytics and their SQL-MapReduce Developer Portal provides a community for sharing best practices and functions which can have an even greater impact to an organization’s business.”

With this announcement Aster Data extends its industry leadership in delivering the most comprehensive analytic platform for big data analytics — not only capable of processing massive volumes of multi-structured data, but also providing an extensive set of tools and capabilities that make it simple to leverage the power of MapReduce analytics. The Aster Data

SQL-MapReduce Developer Portal brings the power of SQL-MapReduce accessible to data scientists, quantitative analysis, and analytic developers by making it easy to share and collaborate with experts in developing SQL-MapReduce analytics. This portal builds on Aster Data’s history of SQL-MapReduce innovations, including:

  • The first deep integration of SQL with MapReduce
  • The first MapReduce support for .NET
  • The first integrated development environment, Aster Data
    Developer Express
  • A comprehensive suite of analytic functions, Aster Data
    Analytic Foundation

Aster Data’s patent-pending SQL-MapReduce enables analytic applications and functions that can deliver faster, deeper insights on terabytes to petabytes of data. These applications are implemented using MapReduce but delivered through standard SQL and business intelligence (BI) tools.

SQL-MapReduce makes it possible for data scientists and developers to empower business analysts with the ability to make informed decisions, incorporating vast amounts of data, regardless of query complexity or data type. Aster Data customers are using SQL-MapReduce for rich analytics including analytic applications for social network analysis, digital marketing optimization, and on-the-fly fraud detection and prevention.

“Collaboration is at the core of our success as one of the leading providers, and pioneers of social software,” said Navdeep Alam, director of Data Architecture at Mzinga. “We are pleased to be one of the early members of The Aster Data SQL-MapReduce Developer Portal, which will allow us the ability to share and leverage insights with others in using big data analytics to attain a deeper understanding of customers’ behavior and create competitive advantage for our business.”

SQL-MapReduce is one of the core capabilities within Aster Data’s flagship product. Aster DatanCluster™ 4.6, the industry’s first massively parallel processing (MPP) analytic platform has an integrated analytics engine that stores and processes both relational and non-relational data at scale. With Aster Data’s unique analytics framework that supports both SQL and
SQL-MapReduce™, customers benefit from rich, new analytics on large data volumes with complex data types. Aster Data analytic functions are embedded within the analytic platform and processed locally with data, which allows for faster data exploration. The SQL-MapReduce framework provides scalable fault-tolerance for new analytics, providing users with superior reliability, regardless of number of users, query size, or data types.


About Aster Data
Aster Data is a market leader in big data analytics, enabling the powerful combination of cost-effective storage and ultra-fast analysis of new sources and types of data. The Aster Data nCluster analytic platform is a massively parallel software solution that embeds MapReduce analytic processing with data stores for deeper insights on new data sources and types to deliver new analytic capabilities with breakthrough performance and scalability. Aster Data’s solution utilizes Aster Data’s patent-pending SQL-MapReduce to parallelize processing of data and applications and deliver rich analytic insights at scale. Companies including Barnes & Noble, Intuit, LinkedIn, Akamai, and MySpace use Aster Data to deliver applications such as digital marketing optimization, social network and relationship analysis, and fraud detection and prevention.


About Teradata
Teradata is the world’s leader in data warehousing and integrated marketing management through itsdatabase software, data warehouse appliances, and enterprise analytics. For more information, visitteradata.com.

# # #

Teradata is a trademark or registered trademark of Teradata Corporation in the United States and other countries.

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Revolution releases R Windows for Academics for free

Logo for R
Image via Wikipedia

Based on the official email from them, God bless the merry coders at Revo-

Revolution Analytics has just released Revolution R Enterprise 4.3 for 32-bit and 64-bit Windows, a significant step forward in enterprise data analytics.  It features an updated RevoScaleR package for scalable, fast (multicore), and extensible data analysis with R. Revolution R Enterprise 4.3 for Windows also provides R 2.12.2, and includes an enhanced R Productivity Environment (RPE), a full-featured integrated development environment with visual debugging capabilities. Also available is an updated Windows release of our deployment server solution, RevoDeployR 1.2, designed to help you deliver R analytics via the Web.

As a registered user of the Academic version of Revolution R Enterprise for Windows, you can take advantage of these improvements by downloading and installing Revolution R Enterprise 4.3 today. You can install Revolution R Enterprise 4.3 side-by-side with your existing Revolution R Enterprise installations; there is no need to uninstall previous versions.

 

High Performance Analytics

Marry Big Data Analytics to High Performance Computing, and you get the buzzword of this season- High Performance Analytics.

It basically consists of Parallelized code to run in parallel on custom hardware, in -database analytics for speed, and cloud computing /high performance computing environments. On an operational level, it consists of software (as in analytics) partnering with software (as in databases, Map reduce, Hadoop) plus some hardware (HP or IBM mostly). It is considered a high margin , highly profitable, business with small number of deals compared to say desktop licenses.

As per HPC Wire- which is a great tool/newsletter to keep updated on HPC , SAS Institute has been busy on this front partnering with EMC Greenplum and TeraData (who also acquired  SAS Partner AsterData to gain a much needed foot in the MR/SQL space) Continue reading “High Performance Analytics”