"Develop a list of resources you might use to gather historical economic data as well as economic forecast data" Essays and Research Papers

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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    Economic

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    MANAGERIAL ECONOMICS MEANING OF MANAGERIAL ECONOMICS Managerial economics‚ used synonymously with business economics‚ is a branch of economics that deals with the application of microeconomic analysis to decision-making techniques of businesses and management units. It acts as the via media between economic theory and pragmatic economics. Managerial economics bridges the gap between ’theoria’ and ’pracis’. The tenets of managerial economics have been derived from quantitative techniques such as regression

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    Data Mining

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    university CASE STUDY OF DATA MINING Summitted by Jatin Sharma Roll no -32. Reg. no 10802192 A case study in Data Warehousing and Data mining Using the SAS System. Data Warehouses The drop in price of data storage has given companies willing to make the investment a tremendous resource: Data about their customers

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    Data Communicatio

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    Quiz 2 True/False Indicate whether the statement is true or false. ____ 1. A good project manager knows how to develop a plan‚ execute it‚ anticipate problems‚ and make adjustments. ____ 2. The most critical element in the success of a system development project is user involvement. ____ 3. The work breakdown structure (WBS) is key to a successful project. ____ 4. Gantt charts become useless once the project begins. ____ 5. Project feasibility analysis is an activity that verifies

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    First two lectures about big data. So why this surge? Isn’t about data at all Systems being able to process data Tools exploit and derive valuable nuggets NOT NEW: Walmart Wallstreet decades Why not out? Competition Teradata 20 years‚ contest MR patent Digital exhaust incr Know your Stats‚ gaga tweet sentiment analysis Correlation causation 2 Old: Centralized systems (data came from humans) Sun hardware Oracle software Moore’s law -> data grew. Data exhausts growing larger. Can’t

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    Hbl Data

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    HABIB BANK LIMITED PAKISTAN Introduction Habib Bank Limited (commonly referred to as "HBL") (Arabic: حَبيب بينك) is the largest bank in Pakistan and a thoroughly established banking chain throughout the world. An extensive network of 1425 branches in Pakistan and 55 international branches makes it one of the largest banks in Pakistan today. Habib Bank Plaza located in Karachi‚ Sindh is the formal headquarters of the bank. The bank has a network outside Pakistan including USA‚ UK‚ Middle East

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    Big Data

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    billion bytes of data in digital form be it on social media‚ blogs‚ purchase transaction record‚ purchasing pattern of middle class families‚ amount of waste generated in a city‚ no. of road accidents on a particular highways‚ data generated by meteorological department etc. This huge size of data generated is known as big data. Generally managers use data to arrive at decision. Marketers use data analytics to determine customer preferences and their purchasing pattern. Big data has tremendous potential

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    Secondary Data

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    Q) What are Secondary Data? Secondary Data Secondary data is information gathered for purposes other than the completion of a research project. Data previously collected by someone else‚ possibly for some other purpose that can be used later for making decisions if found suitable for the purpose‚ other than the original one. Secondary data can be acquired from the internal records of the organization‚ their departments‚ subsidiaries or sister organizations and also from external sources‚ such

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    Data Integration

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    Project Manager: Charter approval date: Project and Module Data Project Brian Norton‚ President Liam Duffy‚ IS Services Document Control Date 30-01-12 02-02-12 10-02-12 16-03-12 Version V 1.0 V 2.0 V 3.0 V 4.0 Changed by Liam Duffy Liam Duffy Liam Duffy Liam Duffy Reasons for Change Original Document Consultation with Sponsor Consultation with Project Board Consultation with Project Board Distribution List Name Brian Norton David Scott Michael Mulvey Noel O’Connor

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    Data Masking

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    An Oracle White Paper July 2010 Data Masking Best Practices Oracle White Paper—Data Masking Best Practices Executive Overview ........................................................................... 1 Introduction ....................................................................................... 1 The Challenges of Masking Data ....................................................... 2 Implementing Data Masking .............................................................. 2

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