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Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

analysis of large data set from disparate sources  available. For a comprehensive analysis of some of the important principles and concepts in-memory technologies, I urge you to read an article titled In-Memory Analytics: A Multi-Dimensional Study written by my colleague Anna Mallikarjunan. Products with in-memory capabilities are not something new to the software industry. For example, the vendor QlikTech started working with their in-memory–based products in the 90s, and other BI application vendors such as IBM Cognos have been using them for more Read More
CRM for Financial and Insurance Markets
Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or&n...
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Documents related to » analysis of large data set from disparate sources


The Role of ERP in Globalization
Globalizing your market reach presents technology and business challenges to profitable growth. Your supply chain strategy for globalization should include an

analysis of large data set from disparate sources  Chapter Three: Implications & Analysis Process and Organization Technology Usage The Importance of Technology Infrastructure User Interface Translating Data International Features Localization Beyond Core ERP Functionality Chapter Four: Recommendations for Action Laggard Steps to Success Industry Norm Steps to Success Best in Class Next Steps Appendix A: Research Methodology Appendix B: Related Aberdeen Research & Tools Figures Figure 1: Business Drivers of Globalization Figure 2: Priorities of Global Read More
About Big Data
There may not be a consensus with respect to just how big

analysis of large data set from disparate sources  of the management and analysis of your vast amounts of data, and focus on it. Identify your needs clearly. Before starting to explore a list of vendors, evaluate the type of technology and information you will require. Once you start to explore your options, make sure you understand your data problem and what you need in order to solve it. Don’t rush; plan. Make sure you are aligning your big data initiative with your corporate goals, and be sure the benefits and risks are clear. Clear the path to Read More
Comparing the Total Cost of Ownership of Business Intelligence Solutions
For many companies, traditional business intelligence (BI) software is costly and resource-intensive. So are open source alternatives that require significant

analysis of large data set from disparate sources  This allows for the analysis of changes in the status of records and the effect on various metrics or outcomes. Proper treatment of snapshot data versus transactional data is critical for most real business analysis as well as being able to easily manage snapshot policy. These various mechanisms require detecting whether a source data record should change an existing analytical data record, add a new record, or record a snapshot correlated with previous ones. The ability to do this drives powerful Read More
The Evolution of a Real-time Data Warehouse
Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine

analysis of large data set from disparate sources  organization. It eases the analysis of future trends. Basic Principles to Consider With the growing popularity and increasing implementation of real-time data warehouses, it is important to consider some basic principles when considering a real-time data warehouse implementation. Data on Time, at the Right Time . The data must flow to the real-time data warehouse at the necessary speed in order to be considered valuable data. In a real-time data warehouse, the ETL batch mechanism based on a table or file Read More
Managing Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses
To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if

analysis of large data set from disparate sources  Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if managing IT is not your core competence, what are your options? A managed service provider (MSP) can help. Learn about the benefits of outsourcing data center management, and make sure your crucial business applications are always available wh Read More
Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and

analysis of large data set from disparate sources  Center Automation With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands. Read More
Phoenix Data Systems
Established in 1974 and currently headquartered in Southfield, Michigan (US), Phoenix DataSystems, Inc., initially began as a custom software developer. In the

analysis of large data set from disparate sources  Phoenix Data Read More
Data Quality: A Survival Guide for Marketing
Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge

analysis of large data set from disparate sources  Quality: A Survival Guide for Marketing Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more. Read More
Melissa Data


analysis of large data set from disparate sources   Read More
Transactional Data: Driving Real-Time Business
A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business

analysis of large data set from disparate sources  Data: Driving Real-Time Business A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more. Read More
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

analysis of large data set from disparate sources  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More
Data Quality Basics
Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at

analysis of large data set from disparate sources  Quality Basics Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue. Read More
The Impact of CRM and Sales Process: Monetizing the Value of Sales Effectiveness
To work through all the issues necessary to improve sales performance, executives have a number of options for leveraging people and knowledge. However, an area

analysis of large data set from disparate sources  Impact of CRM and Sales Process: Monetizing the Value of Sales Effectiveness To work through all the issues necessary to improve sales performance, executives have a number of options for leveraging people and knowledge. However, an area that shows significant potential for helping sales teams meet or exceed their goals is the effective alignment of sales process and technology. Executives looking to optimize performance should consider this approach to achieve their goals. Read More

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