Click to learn more about author Nati Shalom. From its origin in the free software movement, open-source software has grown in popularity and adoption across industries worldwide. Open-source Linux now runs the majority of the world’s server workloads, Kubernetes (and Docker) adoption is growing exponentially and pushing the container and cloud-native revolutions, and on the storage front, much of the innovation in big/fast data was delivered by open-source projects such…

Click to learn more about author Maarit Widmann. A complete time series analysis application covers the steps in a Data Science cycle from accessing to transforming, modeling, evaluating, and deploying time series data. However, for time series data the specific tasks in these steps differ in comparison to cross-sectional data. For example, cross sectional data are collected as a snapshot of one object at one point of time, whereas time series…

Click to learn more about author Avee Mittal. Data cleansing is an important step to prepare data for analysis. It is a process of preparing data to meet the quality criteria such as validity, uniformity, accuracy, consistency, and completeness. Data cleansing removes unwanted, duplicate, and incorrect data from datasets, thus helping the analyst to develop accurate insight. Organizations today are sitting on a pile of data. Most of them use…

Click to learn more about author Piyush Goel. What is a BI tool? Which BI tool is best for your organization? Which criteria should be kept in mind while comparing the different BI tools? Business intelligence (BI) tools transform the unprocessed data into meaningful and actionable insight. BI tools analyze the data and convert them into a presentable and analytical data set in the form of reports, dashboards, etc. By…