CSC215 Data Analytics 2018 A. Fill in the blanks (4 points) ) is data whose seale, distribution, diversity and/or timeliness require the use of new technical architectures and analytics to enable insights that unlock new sources of business value. to measure past performance and inform business planning. measure your business. They are commonly defined within the OLAP schema. ) focuses on using a consistent set of metrics ) that reflect the most essential metrics to 4. refers to a combinatio n of analytical and machine learning techniques used for drawing inferences and insight out of data. 5. Both and organizations to meet these emerging business challenges successfully are needed for Criteria for Big Data Projects: be iterative and flexible called ( volume of data and its complexity. These conditions give rise to complex analytical 6. The analytic techniques being used in this context need to ), due to the high projects that can be performed with some latency, during the steps, the ) is needed, or by operationalizing these analytical techniques using a combination of advanced analytical methods, big data and machine learning algorithms to provide real time, it requires ( or near real time analysis. ): Data assets gathered from multiple sources and technologies for analysis; Enables high performance analytics using in database processing; Reduces costs associated with data replication into "shadow" file systems ) is the process of stating the analytics problem to be solved : Data containing a defined data type, format, structure