Data Vectorization — Learn free

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Questions 1–10 of 10

1. What is Data Vectorisation about?
Question 1A. Compressing data so it occupies less disk spaceB. Enabling parallel processing to fetch dataC. Converting text into numeric vectors for searchD. Encrypting data before it leaves a nodeE. Sorting data before it is queried
2. In which processing mode does a computer or server traditionally work?
Question 2A. MIMDB. SIMDC. MISDD. SISDE. MPP
3. When Data Vectorisation switches a system into MPP mode, which instruction model does it adopt?
Question 3A. MISDB. SIMDC. SISDD. MIMDE. OLTP
4. In Data Vectorisation, what happens when one query is executed and the data resides in multiple data nodes?
Question 4A. Data from all nodes is pulled in parallelB. Each node is queried one after anotherC. Only the first node is readD. The query is rejected until the data is consolidatedE. The data is first copied to a single node
5. Since which developments has Data Vectorisation become a key component of data solutions?
Question 5A. Floppy drives, cables and desktopsB. Mainframes and punched cardsC. Hadoop, NoSQL databases and CloudD. Oracle Forms and SSRSE. OLAP cubes and MDX
6. Which kinds of datasets created the need for Data Vectorisation in the Big Data era?
Question 6A. Small reference tablesB. Development test dataC. Spreadsheets and CSV exportsD. Canned reportsE. Social media, CCTV and audio datasets
7. Why was non-vectorised processing unsuitable for huge datasets?
Question 7A. Because it cannot handle structured dataB. Because it requires a cloud subscriptionC. Because it is incompatible with SQLD. Because processing gigabytes and terabytes sequentially would take daysE. Because it produces less accurate results
8. How much faster does Data Vectorisation make computation compared with SISD, according to *I Am Datapedia!*?
Question 8A. About twice as fastB. About ten times fasterC. Hundreds of times fasterD. Exactly as fast but cheaperE. Slightly slower but more reliable
9. Which two of the four instruction models does the Data Vectorisation discussion focus on?
Question 9A. SISD and SIMDB. MISD and MIMDC. SIMD and MIMDD. SISD and MISDE. SIMD and MISD
10. Which statement about Data Vectorisation is NOT correct?
Question 10A. It was in use before Big Data but was not famousB. It explains how MPP works at the back endC. Most databases are now vectorisation or MPP enabledD. It became common since the inception of Big Data or HadoopE. It can only be used with structured relational data