Garbage In, Garbage Out”: Importance of Data Quality in Analytics and Its Implications

by Karen Orbista

Posted on 2020-10-30



Data Analytics is the process of analyzing raw data in order to generate statistics, identify patterns, and provide meaningful insights out of it. With the help of technology, it is easier to perform such analysis, especially for big data, and make visualizations for the viewers to see what the data are trying to convey. But how sure are they that those data are in good quality? Why is it important to check for the quality of the data?

Ensuring good data quality might be hard but one should take the importance of data quality into account whenever they are going to analyze data. Accessibility, accuracy, completeness, consistency, relevance, and reliability are some factors that could be considered before, during, and after performing the data analysis.

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Time Series Analysis

by Karl Anton Retumban

Posted on 2020-10-27



Time series analysis is a set of techniques and methods in analyzing data points ordered by time. A sequenced observations or data points ordered or indexed by time is called time series data. Some examples of a time series data are monthly sales, quarterly GDP of the Philippines, hourly stock prices of PSEi indices, daily Peso-Dollar exchange rate and annual rainfall in Manila.

Various techniques and methods are available in the time series analysis domain in relation to extracting insights, determining relationships and explaining an underlying phenomenon. Depending on the goal, we can take on various ap

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Analytics as Part of Business Strategy

by admin

Posted on 2020-09-01



In the current business environment, no business decision can be made and executed if it is not supported by data. Almost all company decisions are backed by hard numbers. In the past, recommendations from industry experts is often enough to make strategic decisions, but nowadays, any recommendations, even from veteran industry experts cannot hold ground if it’s not supported by cold numbers.

   

 

 

 

 

 

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Data Visualization in Business Intelligence

by Darrell Beltran and Arvin Fernandez

Posted on 2020-09-01



Business Intelligence (BI) is a set of methods, processes, architectures, applications and technologies that gather and transform raw data into meaningful and useful information used to enable more effective insights generation and decision-making to drive business performance.

Data visualization has been rising rapidly for the past few years in the Business Intelligence and Analytics industry. It is also a big part of data science which has gained wide popularity recently.

Data visualization is the visual and interactive exploration and graphic representation of data of any size, type or origin. The purposes of visualizing data are multifold, ranging from general comprehension and understanding of ideas, supporting informatio

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