Forgot password?
|
|
|
|
Home
We were unable to sign you in.
Please verify your user name and password and try again. If you do not have a TEC account, register now.

Free software comparison template sample

Featured Documents related to » big data


Core PLM Product Data and Recipe Management--Process RFP Templates
Core PLM Product Data and Recipe Management--Process RFP Templates
RFP templates for Core PLM Product Data and Recipe Management--Process help you establish your selection criteria faster, at lower risks and costs.


Product Data Management (PDM) RFP Templates
Product Data Management (PDM) RFP Templates
RFP templates for Product Data Management (PDM) help you establish your selection criteria faster, at lower risks and costs.


Tibco vs Oracle Data integration
Tibco vs Oracle Data integration
Compare ERP solutions from both leading and challenging solutions, such as Tibco and Oracle Data integration.


Documents related to » big data


Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

BIG DATA:
9/9/2009 2:32:00 PM

Developing a Universal Approach to Cleansing Customer and Product Data
Developing a Universal Approach to Cleansing Customer and Product Data. Find Free Proposal and Other Solutions to Define Your Acquisition In Relation To Cleansing Customer and Product Data. Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

BIG DATA:
6/1/2009 5:10:00 PM

Achieving a Successful Data Migration
Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for Achieving a Successful Data Migration. The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

BIG DATA:
10/27/2006 4:30:00 PM

Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g for Data Warehousing and Business Intelligence. Find RFP Templates and Other Solutions to Define Your Project In Relation To Oracle Database, Data Warehousing and Business Intelligence. Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

BIG DATA:
4/20/2009 3:11:00 PM

Data Conversion in an ERP Environment
Converting data in any systems implementation is a high wire act. Converting data in an ERP environment should only be undertaken with a safety net, namely a well thought-out plan of execution. This article discusses the guidelines for converting data when considering manual or electronic alternatives.

BIG DATA:
10/21/2002

The Fast Path to Big Data
Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

BIG DATA: Big Data, Big Data architecture, Big Data challenges, Big Data system, Big Data technology.
2/7/2013 12:55:00 AM

Information Life Cycle Management for Business Data
Information Life Cycle Management for Business Data. Find RFP Templates and Other Solutions to Define Your Acquisition In Relation To Information Life Cycle Management. While companies have long seen their stores of data as valuable corporate assets, how they manage those stores varies enormously. Today, however, new government regulations require that companies retain and control information for long periods of time. Find out what IT managers are doing to meet these new regulatory requirements, and learn about solutions for storing vast quantities of data for the lowest possible cost.

BIG DATA:
4/20/2009 3:12:00 PM

How to Use Data Management Successfully
Find out in the white paper master data management: extracting value from your most important intangible asset.

BIG DATA: data management successfully, data, management, successfully, management successfully, data successfully, data management..
6/23/2009

Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

BIG DATA: data mining, web analytics, spss software, web mining, business analytics, data analytics, sql data mining, predictive model, knowledge discovery, web scraping, data mining software, advanced analytics, predictive analytics, predictive modeling, data mining tools, data warehousing concepts, web extract, web scraper, business analysis software, data mining concepts, web data mining, clementine spss, data mine, data mining business, web extraction, statistical consulting, data mining learning, statistical analysis software, data mining research, what is data mining, data mining warehouse, .
3/28/2000

Automation for the New Data Center
Data centers are squeezed by a variety of pressures, such as power consumption, heating, ventilating, and air conditioning (HVAC) requirements, new servers, human error, patching, asset tracking, and more. On top of this, you have to keep up with dynamically changing business requirements. One of the key ways you can address these dilemmas, however, is through server consolidation using virtualization.

BIG DATA:
2/5/2007 9:40:00 AM

Data Discovery Applications » The TEC Blog


BIG DATA: analytics, bi, Business Intelligence, Cognos Insight, data discovery, data discovery applications, endeca, Inetsoft, Lyza, PowerPivot, QlikView, style intelligence, Tableau, TIBCO spotfire, visual intelligence, webfocus visual discovery, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
17-08-2012

Use this index to search for white papers related to commonly used search terms A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Others 
Recent Searches
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Others
A: 1 2 3 4 5 6 7 8 9
B: 1 2 3 4 5 6 7 8
C: 1 2 3 4 5 6 7 8 9 10 11 12
D: 1 2 3 4 5 6
E: 1 2 3 4 5 6 7 8 9
F: 1 2 3
G: 1 2
H: 1 2 3
I: 1 2 3 4 5 6 7 8 9
J: 1
K: 1
L: 1 2 3
M: 1 2 3 4 5 6 7 8
N: 1 2 3
O: 1 2 3
P: 1 2 3 4 5 6 7 8 9 10
Q: 1
R: 1 2 3 4 5
S: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
T: 1 2 3 4
U: 1 2
V: 1 2
W: 1 2 3 4
X: 1
Y: 1
Z: 1
Others: 1 2


©2013 Technology Evaluation Centers Inc. All rights reserved. Search powered by Google