Frequently Asked Questions


Data analytics enables making conclusions while analyzing data from informational resources. Data analytics uses strategies via technological processes and algorithms that manipulate data for human utilization and understanding. Data analytics helps businesses optimize their capacities.

Data analysts manipulate data to help their organizations make decisions. Using strategies from a range of content areas, mathematics, and statistics, data analysts make predictions followed by conclusions which sheds light on future outcomes for business optimization

The difference between analytics and analysis is scalability. Data analytics is a generalized term and is the umbrella over data analysis. Data analysis is the examination of data. Data analysis includes data collection, organization, storage, and strategies and tools used for analysis.

Legacy modernization refers to leveraging and increasing flexibility by maintaining consistency across platforms and addressing IT challenges. Rewriting of a legacy system for software programming is part of legacy modernization as well.

Simplify access to data that is evolving. When more data is available there is better predictability. Therefore, business analysts and data scientists are able to access more data.

If data is easily accessible, predictability increases which supports better outcomes. SAS helps by supporting native data access capabilities, which enables the manipulation of various types of data from differentiated structures and architectures.

Frequently Asked Questions


With an appropriate data analysis process and tools, what was once an overwhelming volume of diverse information becomes a precise, clear decision point.

To enhance your data analysis skills and analyze your decisions, implement these 4 steps in your data analysis process:

Analytics is not just for once or for any special event, it is a continuous process. Businesses should not take their concentration off analytics and prepare to utilize it as a regular business function. Once businesses begin comprehending the potential analytics to resolve problems, they start using all kinds of strategic and general business decisions.


Data is the most essential resource for any analytics project thus the business should make sure that it apprehends its business and customer data in a structured manner. To capture the right data points in the right format requires a long and short term data strategy. This strategy depends on what the company is trying to achieve (e.g. Learn about the customer or product selling strategies, or customer journey etc.) and how. It requires certain sophistication to build in data capturing techniques and technological support that will help us store and these data points in an understandable format.

Predictive analysis is how a business estimates historical data and past performance via analytical algorithms and machine learning techniques so that they predict, and project future outcomes

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