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Record with diagram 400rs., without diagrams 350rs. Observations and assignments 300rs and also any writing work we do.. call me 868686.2142 price negotiable if any other issues call me..if there any problems to meet/ give records we will came infront on you to receive records...

Any type of written records:400rs Observations and assignments or notebooks:300rs Price Negotiable as per pages to be written Note: No Diagrams plzz

Hello guys I am Jaya . I can write records , assignments in a given period of time for affordable prices ... Records will be taken by me and submitted by me in a specified locations in kakinada.. I will upload my handwritten page as a picture.. If interested contact me. Price will be varied according to pages and time period

Type Tutoring "SAP MDM Online Training""contact us: +, By Real Time Experts from Hyderabad, Bangalore,India,USA,Canada,UK, Australia,South Africa." SAP MDM Course Curriculum:- History Of MDM MDM Overview MDM Performance MDM Components:- Server Components Client Components Admin Components MDM Console:- Console Overview Console Settings Console Security Repository Level Server Level MDM Server Management:- Server Security Working with MDM server Working with MDM Repository MDM Repository Management:- Planning Repository Designing Repository Working with tables Main Table Flat Table Hierarchy Table Taxonomy Table Special Tables Object Tables MDM Repository Security:- Console Level Repository Security Roles Users Change Tracking Remote Systems Port Repository Administration:- Duplicating Repository Backup and Restore Compacting Repository Working with master/slave Repository Multilingual Support MDM Data Manager Data Manager Overview:- MDM Modes Record Mode Hierarchy Mode Taxonomy Mode Matching Mode Record Mode: Searching for records:- Drilldown Search Freeform Search Mask Names Search Saved/Local Search Browser Embedding Protecting Records Checkout/In records MDM Expressions Validations Assignments Hierarchy Mode:- Working with hierarchy tables Taxonomy Mode Working with taxonomy tables Creating Categories Creating Attributes and linking Matching Mode:- Transformations Rules Strategies Match & Merge Working with Qualifier tables MDM Workflow MDM Import Manager:- Import Manager Overview Parametric Import Join and Lookup Pivot and Reverse pivot Partitioning Fields Field Mapping Value Mapping Value Conversion Import Maps MDM Syndicator:- Syndicator Overview Parametric Search Field Transformation Data Transformation Record Suppression Syndication Map Map and Map properties Item Mapping Destination Items Merge Items Syndication Records MDM Import Server MDM Syndication Server MDM Automatic process Over View of other MDM tools:- Publisher Image Manager Language Selector

Type Computer 5 levels of training on Big Data Analytics using Hadoop!! What is Big Data?  Everyday, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.  According to IBM, 80% of data captured today are unstructured, from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, to name a few. All of this unstructured data is Big Data. What does Hadoop solve?  Hadoop is the core platform for structuring Big Data, and solves the problem of making it useful for analytics purposes. Who should go for this? Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course. Objectives  Master the concepts of Hadoop Distributed File System  Setup a Hadoop Cluster  Write MapReduce Code in Java  Perform Data Analytics using Pig and Hive  Understand Data Loading Techniques using Sqoop and Flume  Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing  Have a good understanding of ZooKeeper service  Use Apache Oozie to Schedule and Manage Hadoop Jobs  Implement best Practices for Hadoop Development and Debugging  Develop a working Hadoop Architecture  Work on Big Data Analytics and gain Hands on Project Experience To know further details, information on group discounts, In-house training, consulting and corporate nominations for the training, Please Contact jayanthi: / 044-

SAS Clinical Research Trainers required for elegant it services good salary based on training quality 1. History of SAS 2. SAS comes in ERP sector or not? Why? 3. Role of Statistical Analysis in Clinical Research Study and Banking analysis 4. SAS role in Clinical Research Study and Banking analysis 5. Data modeling and Data mining concepts 6. Project management in Clinical Research Study analysis and Banking analysis 7. What is Clinical research Study? 8. What is Protocol and role of Protocol in Clinical Research Study? 9. What is randomization and non randomization? Which is playing 10. Main role in Clinical research study? 11.What is SOP (Standard operating Procedure)? 11. What is DBMS? 12. Role of DBMS team in Clinical Research Study 13. What is CDM (Clinical data management)? 14. Importance of CDM systems for data loading 15. What is SAP (Statistical Analysis Plan)? 16. Role of SAP in Clinical Research Study 17. SAS Work Flow in Clinical Research Study 18. Relation between SAS and DBMS 19. Interaction between SAS with CDMs for data access 20. Various report generation in Clinical Research Study 21. Role of SAS in Credit Analysis and Different Banking Channels 22. When will go any Industry for Data modeling and Data mining 23. Role of SAS in Data modeling and Data mining GETTING STARTED WITH SAS SYSTEMS: 1. Basic operating system commands, operating system file structures 2. Managing windows in SAS window environment 3. How to run SAS application in different modes and in different environment like Windows, Unix and Mainframes. 4. Use of different kind of SAS products and how to use in SAS application. 5. Difference between the SAS products. 6. Why using the SAS in different sectors 7. How to use the Data Step to read and manipulate complex forms of data 8. Write Data and Proc Steps 9. Data step compile and execution 10. To run SAS application on different modes 11. Reading internal raw data into SAS 12. Read any type of external raw data into SAS 13. Reading raw data SAS environment into DATASET using Input statement & advance INFILE Statement options 14. Working with Data Storage in SAS libraries creation for user defined libraries and multi-engine architecture 15. Using a single libref to reference some or all SAS libraries reading and printing mixed records formats 16. Reading packed and zoned decimal data Working with EBCDIC and ASCII data 17. Reading data from dataset to another dataset 18. To manage the SAS window environment use with Global options 19. Reducing memory requirements with BUFFNO and BUFSIZE working with SAS dataset options 20. To manage existing data with controlling statements and expressions 21. Creating summary information, SAS functions, transforming data 22. Changing variable types using the PUT and INPUT functions Summarizing Data Files 23. Generation Data Sets to create historical information SAS 24. To export data from datasets to delimiter files using with dataset block 25. Understand error messages in the SAS log and debug your program 26. Use with error handling concepts Thanks&Regards Elegant IT Services, #nd Floor,Aswath Nagar Varthur main road,Near Railway Fly Over Maratha halli,Land mark: Chemmunar Jewellers,

SAS Clinical research organization oriented training in elegant it services in marathahalli. 1. History of SAS 2. SAS comes in ERP sector or not? Why? 3. Role of Statistical Analysis in Clinical Research Study and Banking analysis 4. SAS role in Clinical Research Study and Banking analysis 5. Data modeling and Data mining concepts 6. Project management in Clinical Research Study analysis and Banking analysis 7. What is Clinical research Study? 8. What is Protocol and role of Protocol in Clinical Research Study? 9. What is randomization and non randomization? Which is playing 10. Main role in Clinical research study? 11.What is SOP (Standard operating Procedure)? 11. What is DBMS? 12. Role of DBMS team in Clinical Research Study 13. What is CDM (Clinical data management)? 14. Importance of CDM systems for data loading 15. What is SAP (Statistical Analysis Plan)? 16. Role of SAP in Clinical Research Study 17. SAS Work Flow in Clinical Research Study 18. Relation between SAS and DBMS 19. Interaction between SAS with CDMs for data access 20. Various report generation in Clinical Research Study 21. Role of SAS in Credit Analysis and Different Banking Channels 22. When will go any Industry for Data modeling and Data mining 23. Role of SAS in Data modeling and Data mining GETTING STARTED WITH SAS SYSTEMS: 1. Basic operating system commands, operating system file structures 2. Managing windows in SAS window environment 3. How to run SAS application in different modes and in different environment like Windows, Unix and Mainframes. 4. Use of different kind of SAS products and how to use in SAS application. 5. Difference between the SAS products. 6. Why using the SAS in different sectors 7. How to use the Data Step to read and manipulate complex forms of data 8. Write Data and Proc Steps 9. Data step compile and execution 10. To run SAS application on different modes 11. Reading internal raw data into SAS 12. Read any type of external raw data into SAS 13. Reading raw data SAS environment into DATASET using Input statement & advance INFILE Statement options 14. Working with Data Storage in SAS libraries creation for user defined libraries and multi-engine architecture 15. Using a single libref to reference some or all SAS libraries reading and printing mixed records formats 16. Reading packed and zoned decimal data Working with EBCDIC and ASCII data 17. Reading data from dataset to another dataset 18. To manage the SAS window environment use with Global options 19. Reducing memory requirements with BUFFNO and BUFSIZE working with SAS dataset options 20. To manage existing data with controlling statements and expressions 21. Creating summary information, SAS functions, transforming data 22. Changing variable types using the PUT and INPUT functions Summarizing Data Files 23. Generation Data Sets to create historical information SAS 24. To export data from datasets to delimiter files using with dataset block 25. Understand error messages in the SAS log and debug your program 26. Use with error handling concepts Thanks&Regards Elegant IT Services, #nd Floor, Aswath Nagar,Varthur main road, Opp Safal Fresh,Near Railway Fly Over Maratha halli,Bangalore