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Cloudera CCP DE575 Data Engineer Hadoop Certification material. 
Total 79 Solved scenarios which includes in depth complex scenarios solved for Sqoop, flume, Hive,Avro,HDFS, OOzie workflow linear, branch, decision, scheduled, coordinator and regular expressions based questions and many more. Its a performance based exam to do hands-on task on CDH5 (Complemenatry Selected videos will be provided to help with this (In progress)   . Practice and Sample Problem with its solutions will be provided in HadoopExam Simulator only (Check Below Video to understand more). In real exam you will be asked many problems which can be solved mixing the components e.g. Hive and Sqoop , flume and HIve, OOzie and Hive etc. We have added complex scenerio as well as step by step solutions and each solution is executed by our technical team to make sure it works perfectly. This problem scnerios not only helps for CCP DE575 Data Engineer exam, but also it will help in becoming Data Engineer using Hadoop eco-system. You can solve similar problems in your daily job. Hence solve these scenarios and become BigData experts, with HandsOn. Once you complete all 73 problem scenarios your own, you will be ready to clear real CCP DE575 exam. This is the one of the most demanding certification among the Hadoop Data Engineer on HadoopExam.com . Technical team is working to add more Tasks, so before appearing real exam please drop an email. So we will provide you update if available and to get notify for update do not forget to Subscribe here

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Features of the CCP DE:575 (Cloudera Hadoop and Spark Developer certification)
1. Entire syllabus will be covered.
2. All questions are scenerio based and step by step solutions will be given
3. Same will be executed by our exper technical team and complimentary selected recorded videos will be shared here. (In progress)
4. Almost all scenerios will be covered for real exams.
5. Any future updates will be free  on single and same machine.
6. Solutions are already executed on Cloudera CDH, hence same can be used for real exam.
7. Our expert regularly update the simulator.
8. It will help you gain confidence and reduce study time.
9.  Always updated and correct/incorrect  way of solutions explanation

Note : This product is tested only on Windows Operating System. IOS users are using this Wine Bottler to run exe.

* Please read faq section carefully



Syllabus for CCP:DE575 (Data Engineer)

Data Ingest
The skills to transfer data between external systems and your cluster. This includes the following:
  1. Import and export data between an external RDBMS and your cluster, including the ability to import specific subsets, change the delimiter and file format of imported data during ingest, and alter the data access pattern or privileges.
  2. Ingest real-time and near-real time (NRT) streaming data into HDFS, including the ability to distribute to multiple data sources and convert data on ingest from one format to another.
  3. Load data into and out of HDFS using the Hadoop File System (FS) commands.
Transform, Stage, Store
Convert a set of data values in a given format stored in HDFS into new data values and/or a new data format and write them into HDFS or Hive/HCatalog. This includes the following skills:
  1. Convert data from one file format to another
  2. Write your data with compression
  3. Convert data from one set of values to another (e.g., Lat/Long to Postal Address using an external library)
  4. Change the data format of values in a data set
  5. Purge bad records from a data set, e.g., null values
  6. Deduplication and merge data
  7. Denormalize data from multiple disparate data sets
  8. Evolve an Avro or Parquet schema
  9. Partition an existing data set according to one or more partition keys
  10. Tune data for optimal query performance
Data Analysis
Filter, sort, join, aggregate, and/or transform one or more data sets in a given format stored in HDFS to produce a specified result. All of these tasks may include reading from Parquet, Avro, JSON, delimited text, and natural language text. The queries will include complex data types (e.g., array, map, struct), the implementation of external libraries, partitioned data, compressed data, and require the use of metadata from Hive/HCatalog.
  1. Write a query to aggregate multiple rows of data
  2. Write a query to calculate aggregate statistics (e.g., average or sum)
  3. Write a query to filter data
  4. Write a query that produces ranked or sorted data
  5. Write a query that joins multiple data sets
  6. Read and/or create a Hive or an HCatalog table from existing data in HDFS
Workflow
The ability to create and execute various jobs and actions that move data towards greater value and use in a system. This includes the following skills:
  1. Create and execute a linear workflow with actions that include Hadoop jobs, Hive jobs, Pig jobs, custom actions, etc.
  2. Create and execute a branching workflow with actions that include Hadoop jobs, Hive jobs, Pig jobs, custom action, etc.
  3. Orchestrate a workflow to execute regularly at predefined times, including workflows that have data dependencies

* Please read faq section carefully.


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