...Membership/ registration No: | | Unique Learner No (ULN) (if applicable): | 535885 | Qualification title: | Certificate in Human Resource Practice | Module title(s): | Recording, Analysing and Using Human Resources Information | Module code(s): | 3RAI F20I3B | Assessment activity (and assignment title if applicable) and the learning outcomes addressed: | Human Resource Management of Data | Date due for assessment: | 11.05.2015 | Extension request date: | N/A | | | Extension granted: | N/A | Actual date evidence submitted: | 08.05.2015 | Revised due date: | N/A | Candidate declaration: | * I confirm that the work/evidence presented for assessment is my own unaided work. * I have read the assessment regulations and understand that if I am found to have ‘copied’ from published work without acknowledgement, or from other candidate’s work, this may be regarded as plagiarism which is an offence against the assessment regulations and leads to failure in the relevant unit and formal disciplinary action. * I agree to this work being subjected to scrutiny by textual analysis software if required. * I understand that my work may be used for future academic/quality assurance purposes in accordance with the provisions of the Data Protection Act 1998. * I understand that the work/evidence submitted for assessment may not be returned to me and that I have retained a copy for my records. * I understand that until such time as the assessment grade has been ratified through...
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...Module 3: Recording, analysing and using HR information 3RAI Kathrina Yarwood Activity 1.1, 1.2, 2.1, 2.2 The storing of data also known as data management is important for any business or organisation. There are several reasons why an organisation would need to store HR data. Any data collected would be invaluable for various reasons including but not limited to compliance, reporting, business planning and budget setting. An organisation or business can collect any number of different types of data including absenteeism information, equality and diversity questionnaires, in respect to compliance and reporting data collected would include absences, retention information and skill set information. Budget setting information would include workforce numbers, revenues and potential business opportunities. One main HR priority is to track and store existing employee data. For an organisation to move forward, to be able to report on staff accurately and if needed to validate the value of teams or certain job roles, Human resources must have a good understanding of the data and also have a suitable system to secure the data. Management at the highest level require data collected by HR departments as the data would be essential to their planning the future direction of the organisation and make them aware of any number of significant issues such as employee retention and enable them to pursue a solution. HMRC can request copies of records collected by HR to ensure that employees...
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...Client Workstations- For client workstations domain we Dominique and Kendal plan to implement full 128 bit hard drive encryption on all users’ desktops, laptops, cellphones, tablets, and Company assigned bring your own devices (byod)’s. for all level 1 security users which includes; employees, contractors, vendors, department & managers, the will be a 90 day password expiration which at the end of 90 day forces the user to change their password and cannot recycle their passwords for 9 months. Each password has to be at least 24 characters with one capitol letter and have at least one symbol and one number in the password. For all level 2 workstations which include network administrators we are going to implement CAC CARDS OR COMMON ACCESS CARDS with a pin for main log in. There will be finger print access required to enter any level 2 security workstation or work are. In order to enter any level 2 work area there will be a required key card for entry. On to our level 3 client workstations include; senior administrators, junior administrators, & the co-ceo & the ceo. We plan on implementing a fingerprint scanner to boot the workstation, a 128 bit hard drive encrypted password to log on. In order to enter a level 3 workstation area users will be required to user a CAC magnetized card, a fingerprint, and must be cleared by 24hr surveillance to enter the level 3 workstations area. Server areas- For Richman investments each server room will have 24 hr...
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...Sorrells 11/30/2012 The 123 Textile Corporation has several solvable issues that we will address in this network updating proposal. They have been exposed to inclement weather and as of late a break in resulting in the companies sever and all pertinent data for sales, production, human resources. This proposal will lay out all necessary hardware upgrades as well as the software upgrades needed to maintain the new hardware. It will also look at off-site back up as a potential resolution to being in an area that may be more susceptible to break-ins resulting in equipment loss and or damage. The proposal will also address the issues of inclement weather and possible protection from natural disasters. Hardware and equipment proposal; A required designated space for the new computer equipment should be around 50 square feet with through wall ventilation but no window or exterior access points. In addition a cable line for modem connection and power source will be required. Power source should be of 20 amp circuit and non GFI, number of circuits at primary location in room to be four. In consideration of power outages that could result in loss of data a recommended solution will be the installation of an online UPS battery backup unit which provides continuous power while plugged in through the unit’s battery allowing for smoother and quicker power transition. This unit provides not only a source of power in the event of power loss but additionally...
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...| Paul D. GIllespie | |North Central Airlines | |Airline Reservation System | |ITEC 630 | |Fall 2008 | | | |11/15/2008 | North Central Airlines Airline Reservation System Proposal Phase 1 Background (Problem Statement): North Central Airlines is a small but growing airline that specializes in providing amenities that major airlines don’t (like children discounts, for example). The corporate executives feel that the Global Distribution System that they currently use and share with larger airlines doesn’t provide the extra services that North Central needs for their business to thrive. Their intent is to design and construct their own Airline Ticketing System....
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...The SCONUL Seven Pillars of Information Literacy Core Model For Higher Education SCONUL Working Group on Information Literacy April 2011 The SCONUL Seven Pillars of Information Literacy: Core Model 2 Introduction In 1999, The SCONUL Working Group on Information Literacy published “Information skills in higher education: a SCONUL position paper” (SCONUL, 1999), introducing the Seven Pillars of Information Skills model. Since then, the model has been adopted by librarians and teachers around the world as a means of helping them to deliver information skills to their learners. However, in 2011 we live in a very different information world and while the basic principles underpinning the original Seven Pillars model remain valid, it was felt that the model needed to be updated and expanded to reflect more clearly the range of different terminologies and concepts which we now understand as “Information Literacy”. In order for the model to be relevant to different user communities and ages, the new model is presented as a generic “core” model for Higher Education, to which a series of “lenses”, representing the different groups of learners, can be applied. At publication (April 2011), only the Core Model and the Research Lens are available. We hope that teachers and librarians representing other learner groups will participate in the development of other lenses. Moira Bent & Ruth Stubbings On behalf of the SCONUL Working Group on Information Literacy. April 2011 ...
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...Training Curriculum Data Warehousing: • Introduction to Business Objects Enterprise Reporting • Fundamentals of Data warehouse Concepts • Introduction to Dimensional Modeling • Developing a Star Schema Reporting: • Building and editing queries with Web Intelligence • Performing on report analysis with Web Intelligence • Filtering Queries using conditions, prompts etc., • Using Combined Queries and merging dimensions • Displaying data in various formats (Ex: Tables, Charts etc.,) Advanced Reporting: • Calculations, Formulas and variables • Ranking Data, using Alerters to highlight data, Formatting numbers and Dates • Understanding Calculation Contexts • Web Intelligence Functions, Operators and Keywords • Calculating values with Smart Measures Universe Designer: • Designer and Universe Fundamentals • Creating a schema with Tables and Joins • Resolving Join problems in a schema • Defining Classes, Objects, hierarchies, using cascading list of values for hierarchies • Testing the universe • Working with OLAP universes Xcelsius 2008: • Application Overview • Creating and Updating Xcelsius visualizations • Using Xcelsius components ( Chart, Containers, Selectors etc.,) • Exporting Xcelsius visualizations to various applications (Power point, PDF, Flash • Creating templates, Alerts and Dynamic visibility • Using Data Manager ( Creating and configuring connections) • Live Office Connections, Query As A Web Service (QWAAS), XML data Connections Crystal...
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...but mitigated by writing to multiple file systems * Data Node * Many per cluster * Manages blocks with data and serves them to Nodes * Periodically reports to Name Node on the list of blocks it stores Map Reduce Nodes * Job Tracker * Task Tracker PIG – A high level Hadoop programing language that provides data flow language and execution framework for parallel computation Created by Yahoo Like a Built in Function for Map Reduce We write queries in PIG – Queries get translated to Map Reduce Program during execution HIVE : Provides adhoc SQL like queries for data aggregation and summarization Written by JEFF from FACEBOOK. Database on top of Hadoop HiveQL is the query language. Runs like SQL with less features of SQL HBASE: Database on top of Hadoop. Real-time distributed database on the top of HDFS It is based on Google’s BIG TABLE – Distributed non-RDBMS which can store billions of rows and columns in single table across multiple servers Handy to write output from MAP REDUCE to HBASE ZOO KEEPER: Maintains the order of all animals in Hadoop.Created by Yahoo. Helps to run distributed application and maintain them in Hadoop. SQOOP: Sqoops the data from RDBMS to Hadoop. Created by Cloudera API to extract data from external databases Pulls data from Hadoop and place it in HIVE Put RDBMS data to HDFS Flume and scoop for distributed reading of large data MAHOUT: Machine learning...
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...The Trusted Information Payoff: Productivity, Performance, and Profits Building an information framework to ensure effective data management produces information that is true, has integrity, and can be trusted. This leads to a continuous improvement culture that can increase employee productivity, improve operational performance, and grow profitability. Karim N. Sidi and Dale A. Hutchinson L arge organizations, especially those that have grown through consolidation, mergers, and acquisitions, are often fraught with incompatible systems and data sources that are costly and difficult to manage. The systems usually do not avail efficient extraction, aggregation, and sharing of data within or across the boundaries of the business process. To address this problem, organizations can turn to an information management framework that facilitates managing raw data to create useful information that can be shared across the organization. SEPTEMBER/OCTOBER 2013 INFORMATIONMANAGEMENT 35 sist of a mix of home-grown, functionspecific applications and third-party systems built by disconnected teams without a shared reference for data definition. The solution – forethought and planning to create well-defined data standards – may appear obvious from an architectural perspective but may not be so easy to accomplish. The steps described below will help. Establish Processes, Rules, Policies Identifying the “truth” first and foremost requires that business processes, rules, and policies...
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...are why, what if, and what next. According to Gartner, BI and Analytics is a $12.2 billion market with 16.4% growth in 2011. Gartner's 2012 CIO survey showed that analytics/BI is the No. 1 technology priority for CIOs. The mega vendors such as Oracle, SAS, IBM etc., are already having major portion of the revenue with their packaged applications in these areas. It is estimated by Gartner that Analytics will be touching 75% of potential users by 2020. This is proven by the growth rate of new vendors such as QlickTech and Tableau by 45% (as per Gartner report). Cloud Storage: Cloud Storage, also referred as Data Storage as a Service, is a delivery of virtualized storage on demand over network. In Cloud Storage, user can perform common operation like create, read, update and delete. In addition, there are other aspects of Cloud Storage like, customer can move or copy the data from one Cloud Storage vendor to another for getting benefits of storage costs and better services. Storage Networking Industry Association (SNIA) has come...
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...White Paper Storage Infrastructures for Big Data Workflows Sponsored by: Prepared by: Eric Slack, Sr. Analyst May 2012 Storage Infrastructures for Big Data Workflows Introduction Big Data is a term used to describe data sets which have grown so large that traditional storage infrastructures are ineffective at capturing, managing, accessing and retaining them in an acceptable time frame. The thing that separates Big Data from simply a large archive is the need to process these data sets or to provide file access to multiple users quickly. Some Big Data use cases involve analytics, the computer-based analysis of large amounts of relatively small data objects, for the purpose of pulling business value from that information. Many of these involve files supporting transaction analysis or automated event processing, such as database or web analytics, which won’t be addressed in this white paper. Instead, this paper will deal with another form of Big Data that supports file processing workflows, often sequential in nature, where large files are shared by knowledge workers to create digital products, support research and perform analysis to increase productivity. Also considered will be Big Data supporting large file analytics in which files are shared by large, high performance compute clusters to support complex analysis and drive business decisions. Big Data File Processing Workflows Some of the industries using large file, Big Data sets in these two use cases include Media and...
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...BUSINESS ANALYTICS Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision making. BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making. Examples of BA uses include: * Exploring data to find new patterns and relationships (data mining) * Explaining why a certain result occurred (statistical analysis, quantitative analysis) * Experimenting to test previous decisions (A/B testing, multivariate testing) * Forecasting future results (predictive modeling, predictive analytics) * FUNCTIONS OF A BUSINESS ANALYST At a high level, a Business Analyst acts as a liaison between business people who have business problems and technology people who know how to create automated solutions. A Business Analyst serves the mission-critical function of understanding specific business needs, determining and documenting accurate requirements from business units and presenting those requirements in a manner that is agreeable, measurable and flexible enough to meet project...
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...DRM, FDM, ODI…OMG Which Tool Do I Use? Edward Roske eroske@interrel.com BLOG: LookSmarter.blogspot.com WEBSITE: www.interrel.com TWITTER: ERoske Introduction to EPM Architect: Cheaper…Faster…Better Edward Roske eroske@interrel.com BLOG: LookSmarter.blogspot.com WEBSITE: www.interrel.com TWITTER: ERoske Thinking Outside the Cube: NonFinancial Applications of Oracle Essbase Edward Roske eroske@interrel.com BLOG: LookSmarter.blogspot.com WEBSITE: www.interrel.com TWITTER: ERoske About interRel Reigning Oracle Titan Award winner – EPM & BI Solution of the year 2008 Oracle EPM Excellence Award 2009 Oracle EPM/BI Innovation Award One of the fastest growing companies in the world (Inc. Magazine, ‟08 & ‟09 & „10) Two Hyperion Oracle ACE Directors and one Oracle Ace Founding Hyperion Platinum Partner; now Oracle Platinum Partner Focused exclusively on Oracle Hyperion EPM software Consulting Training Infrastructure and Installation Support Software sales 4 7 Hyperion Books Available: Essbase (7): Complete Guide Essbase System 9: Complete Guide Essbase System 9: End User Guide Smart View 11: End User Guide Essbase 11: Admin Guide Planning: End Users Guide Planning: Administrators To order, check out www.LuLu.com •5 •Copy right © 2007, Hy perion. All rights reserv ed. Select interRel Customers 6 Abstract DRM, FDM (or is it FDQM), ODI, ERPI, EPMA…thanks, Oracle, for all of these tools but which tool...
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...According to Lee, the most popular definition is a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process (2014). Basically a data warehouse is a copy of transaction data specifically structured for query and analysis. According to Frand, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cut costs, or both (1997). There are many benefits of data warehousing. Yes, it will cost large amounts of money from businesses to have a data warehouse but, in the long run it is worth it to have in a corporation. One benefit is that data warehouses stores and presents information in a way that allows management to make important decisions (Prathap, 2014). Management and even executives can look at the business as a whole instead of by each department. According to Prathap, another benefit of data warehouses is their ability to handle server tasks connected to querying which is not used in most transaction systems (2014). Creating queries and reports can take time and with data warehousing, the server can handle the tasks in a timely fashion. Again, according to Prathap, one of the most important benefits of data warehouses is that they set the stage for an environment where a small amount of technical knowledge about databases...
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...Business Intelligence and Data Warehouses Kevin Gainey Mr. Brown CIS 111 Data warehouses support business decisions by collecting, consolidating, and organizing data for reporting and analysis with tools such as online analytical processing (OLAP) and data mining. Although data warehouses are built on relational database technology, the design of a data warehouse database differs substantially from the design of an online transaction processing system (OLTP) database. The topics in this paper address approaches and choices to be considered when designing and implementing a data warehouse. The paper begins by contrasting data warehouse databases with OLTP databases and introducing OLAP and data mining, and then adds information about design issues to be considered when developing a data warehouse with Microsoft® SQL Server™ 2000. A data warehouse supports an OLTP system by providing a place for the OLTP database to offload data as it accumulates, and by providing services that would complicate and degrade OLTP operations if they were performed in the OLTP database. Without a data warehouse to hold historical information, data is archived to static media such as magnetic tape, or allowed to accumulate in the OLTP database. If data is simply archived for preservation, it is not available or organized for use by analysts and decision makers. If data is allowed to accumulate in the OLTP so it can be used for analysis, the OLTP database continues to grow in size and...
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