Data Blending andIntegration — Learn free

Self-check

Questions 1–10 of 10

1. What is Data Integration?
Question 1A. Merging datasets into a single presentation viewB. Deleting duplicate records from a warehouseC. Connecting with one or more source systems to pull dataD. Building a dashboard for business usersE. Encrypting data in transit between systems
2. What is Data Blending?
Question 2A. Merging all datasets into one viewable and understandable presentation view to answer business KPIsB. Pulling data from a single source systemC. Storing raw data in a Data LakeD. Removing special characters from text fieldsE. Assigning access rights to tables
3. How are Data Integration and Data Blending related?
Question 3A. Data Blending is the prerequisite for Data IntegrationB. They are two names for the same processC. Data Blending replaces Data Integration in a Data LakeD. Data Integration is the prerequisite process for Data BlendingE. They are performed by different departments and never interact
4. What single goal do Data Science, Business Intelligence and every kind of Analytics all work towards, according to I Am Datapedia!?
Question 4A. Reducing storage costsB. Achieving one or another business KPIC. Replacing the IT departmentD. Building the largest possible Data LakeE. Automating data entry
5. In the product-sales example, a product is sold from a shop, an online website and a mobile application. Why is this a blending challenge?
Question 5A. Because the product has a different price in each channelB. Because only the shop stores its data in a databaseC. Because the website has no transaction dataD. Because a Data Warehouse cannot hold more than one channelE. Because the different systems may store transactions in different ways, yet all must be gathered into one target table
6. What does the development team create during the Blending process?
Question 6A. Joins, unions and other transformation logic to convert all transaction types into one standardised listB. New source systems for each sales channelC. A separate warehouse for every channelD. Access policies for business usersE. A backup of every source table
7. In a nutshell, what does the Blending process assist with?
Question 7A. Compressing historical dataB. Presenting standardised data in dashboards and reports for business users' decision makingC. Granting authentication to new employeesD. Pulling raw data from source systemsE. Choosing a NoSQL database
8. Which sources of data are mentioned as possible inputs to blending in the current era?
Question 8A. Only relational databasesB. Only spreadsheets and CSV filesC. Social media, videos, audios, PDFs and emailsD. Only data warehousesE. Only mobile applications
9. What has made it possible to blend structured, semi-structured and unstructured data into one comprehensive view?
Question 9A. The retirement of Data WarehousesB. The use of a single sales channelC. The end of social media dataD. The introduction of Data LakesE. The five-KPI dashboard rule
10. Which statement about Data Integration and Data Blending is NOT correct?
Question 10A. They are core to the Data PipelineB. They are commonly confused with each otherC. In the product example the target system is a Data WarehouseD. Blending produces a standardised list of transactionsE. Blending can be done without first integrating data from source systems