The power of data is provided at fingertips by Tableau in feature-rich visualizations which helps in making data-driven decisions. To make this more effective we need enriched data sets which are provided by the self-service data analytics platform Alteryx. Alteryx Designer helps in discovering, preparing, blending and analyzing data quickly. It allows to perform advanced […] The post Publishing Alteryx .hyper output to Tableau Server appeared first on Visual BI Solutions ..read more

The power of data is provided at fingertips by Tableau in feature-rich visualizations which helps in making data-driven decisions. To make this more effective we need enriched data sets which are provided by the self-service data analytics platform Alteryx. Alteryx Designer helps in discovering, preparing, blending and analyzing data quickly. It allows to perform advanced predictive modelling and spatial analysis on data in an intuitive drag and drop workflow. The output data can be used in Tableau to deliver smarter and impactful visualizations for your enterprise. These functionalities make ..read more

Calgary is a list count-based data retrieval engine which uses indexing methodology to read the data faster. To make it simple you can say as each value of a column is assigned to an index value and maintained as a data structure and values of each column are stored in a separate directory. When you want to read the data, the engine reads the required structure and joins the columns based on the index and creates the output. While working with big data files of volume over 100 million records, time taken to process them will be a major concern. You will not have all day to generate a report fo ..read more

For Alteryx developer, it is good to know the advantage of using Calgary DB over other flat files. It will ramp up your workflow performance. As mentioned in the Alteryx forum, Calgary is a data retrieval engine to perform analysis on a large dataset using indexing methodology. This blog compares Alteryx DB, Calgary DB and CSV in varies scenarios. To demonstrate each scenario, we have taken dataset which contains eleven million records. Scenarios to Compare We have taken the below scenarios based on the tools available in Calgary Creation Creating CSV Creating Alteryx DB Creating Calgary DB D ..read more

Maintaining the master data change over time to ease the reporting for end-user is an unavoidable step in a data model. To handle this, we need to maintain a dimension as a slowly changing dimension which stores current data and the history data with a reference date. There are three ways to maintain the slowly changing dimension which is listed below: Type 1: Overwriting the existing data Type 2: Creating an additional record with the current value Type 3: Creating an additional field that stores the value in the target as previous value and the current value is updated in the original field ..read more

Understanding customers helps a lot while doing business with them. Knowing their patterns and their needs, we can customize the product line accordingly and suggest products to them making a win-win situation for all. Alteryx provides a set of tools in doing behavioral analysis with customer data. It allows to create profiles on a dataset, compare them and analyze their buying behaviour. It uses Solo cast engine which can be obtained from Alteryx by subscription. Solocast engine is a state-of-the-art mining tool developed by Alteryx used for cluster coding and reporting on the behavioral anal ..read more

Reports make end-user to consume data in an efficient manner. Also, it gives a significant impact on organizations decision. One can create a report for several reasons some of them were to monitor resource utilization, productivity assessment, shows business performance across the different period, reveal hindrance of the business process, shows key performance indicator. To achieve this, Alteryx provides a variety of tool to develop the Reports. A report encompasses elements like logo, header, footer, text, images, maps and visuals. Let discuss the tools available for creating these reportin ..read more

Being ready for any possible outcome of the future is always better than facing everything on the go. That’s where forecasting places a major role to make predictions based on past and present data.   ARIMA data Models ARIMA stands for Auto-Regressive Integrated Moving Average mode of forecasting the data across a specific time period. We can create a predictive model for our data by performing any one or combining any of these three methods on the data based on our requirement with this method.   Non-Seasonal ARIMA Models The model names are defined as ARIMA(p,d,q). p is the number of aut ..read more

Data cleansing is a part of data wrangling by which the data is transformed in order to get meaningful analysis. Uncleansed data may contain unwanted characters, null values, unformatted categorical values which may result in misguided decision making. Depending on the data pattern, replacing quantitative nulls with statistically derived values may avoid significant variation in the analysis. Data Cleansing is a necessary preprocessing step in most areas including, Machine learning Data Prediction Data Analysis and Reporting Data Cleansing can be performed in Alteryx using tools like Data Clea ..read more

Orchestrating the data on time-based characteristics is an important task while you are analyzing the progress of your work. While we are dealing with the time characteristics, the Data Time Tool will be handy to deal with different date formats. Let say we have two data sets which have a daily sales order data in every store and a monthly target to achieve in each store. We need a daily report which will have the target that needs to be met in the remaining days of the month.   In this case, we will be using Running Total Tool, to find the progress of the actual sales from which we can calcu ..read more