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RapidMiner Data Engineering Professional Certification Exam Quiz Answers

  • To prevent RapidMiner from overwriting data in the Excel spreadsheet
  • To import data from other spreadsheets with the same metadata without going through the Import Data wizard again
  • To share the spreadsheet data with a colleague
  • To ensure that RapidMiner reads the data as Excel, rather than CSV
  • use the Adjust Date operator with adjustment=-7 and date unit=Day
  • use the Generate Attributes operator with the function ‘ date_add(date,-1,DATE_UNIT_WEEK) ‘
  • use the Date to Numerical operator, subtract the number of milliseconds in one week, and then use the Numerical to Date operator
  • none of the above methods are able to create this new attribute in RapidMiner Studio
  • to transform a text attribute into multiple numerical attributes for future modeling
  • to identify common topics from the entire corpus
  • to create an association rule graph
  • to ascertain the quality of the text prior to modeling
  • use the Reorder Attributes and the Generate Aggregation operator.
  • use the Generate Concatenation operator.
  • use the Generate Attributes operator and the concat function.
  • use the Pivot operator.
  • inner
  • left
  • right
  • outer
  • Which of the two processes shown below will product this result? (Select one)
  • Option A
  • Option B
  • watching Rat Race week I noticed cheeks sore
  • after watch rat race last week i notic my cheek were sore
  • After After_watching watching watching_Rat Rat Rat_Race Race Race_last last last_week week week_I I I_noticed noticed noticed_my my my_cheeks cheeks cheeks_were were were_sore sore
  • After watching Race last week noticed cheeks were sore
  • It will create a new visualization called “Normalization”.
  • It will execute a Jupyter notebook called “Normalization”.
  • It will create a new building block called “Normalization”.
  • It will execute “Normalization” as an embedded process.
  • use the Nominal to Date operator with date format = ‘yyyy-MM-dd HH:mm:ss’
  • use the Numerical to Date operator with no time offset
  • use the Generate Attributes operator with the expression = ‘date_parse_custom(date,”yyyy-MM-dd HH:mm:ss”) ‘
  • add a new Turbo Prep subprocess with a ‘Change to date and time’ Transformation and format = ‘yyyy-MM-dd HH:mm:ss’
  • Option A
  • Option B
  • Option C
  • Option D
  • to read/write file objects in Amazon S3
  • to read/write ExampleSets in Amazon S3
  • to read/write processes in Amazon S3
  • to stream databases in Amazon S3
  • add the Rename by Replacing operator to your process, replacing the “_” character with nothing in the Parameters panel.
  • add the Rename operator to your process, entering each “old” and “new” attribute name in the Parameters panel.
  • go to Turbo Prep, rename the attributes, commit the transformations, and then add the result to your process.
  • add the Rename by Generic Names operator to your process, entering the “_” character as the generic name stem in the Parameters panel.
  • grouping operators into subprocesses
  • attaching colored notes to operators
  • adding colored notes to a process
  • editing the default names of operators in a process
  • None of the above
  • date
  • transaction_id, customer_id, product_id, amount
  • customer_id, product_id, amount
  • customer_id, product_id, date, amount
  • churn
  • id
  • label
  • prediction
  • use the Delete Attributes operator.
  • use the Select Attributes operator and check the ‘invert selection’ option in the Parameters panel.
  • use the Filter Attributes operator.
  • use the Select Attributes operator and choose the subset of desired attributes in the Parameters panel.
  • Option A
  • Option B
  • Option C
  • Option D
  • 1
  • 2
  • 3
  • 4
  • Generate Function Set
  • Auto Model
  • Generate Attributes
  • Turbo Prep → Generate
  • Group by=’Product Category’, Column grouping=’Units Sold’, Aggregation=sum of ‘State’
  • Group by=’State’, Column grouping=’Product Category’, Aggregation=sum of ‘Units Sold’
  • Group by=’Product Category’, Column grouping=’Units Sold’, Aggregation=sum of ‘State’
  • Group by=’State’, Column grouping=’Units Sold’, Aggregation=sum of ‘Product Category’
  • use the Manage Database Connections wizard each time you run the process.
  • use the Update Database operator to refresh the data, and then use the Read Database operator.
  • use the Read Database operator to retrieve data from the table each time you run the process.
  • always ensure that you have the most recent JDBC drivers installed in RapidMiner Studio.
  • Option A
  • Option B
  • Option C
  • Option D

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