Flow Data Automation & Analytics Blog

Doing Data Quality With Flow

In this article, I provide an introduction to measuring and evaluating data quality using Flow. I briefly discuss data quality dimensions and data quality assessment. Then I examine how a schema-on-write approach increases the time and cost required to assess data quality along with a brief discussion of schema-on-read technology. I then introduce Flow's "Generic Data" technology as a solution to the deficiencies of schema-on-write and schema-on-read for data quality. Finally, I provide a hands-on working example of doing data quality in Flow using some sample name and address data.

A Reusable Benford Analysis Flow

In this post, we build a reusable eight-step Flow that performs a basic Benford's Analysis on a sample data set. This Flow loads the sample data set then obtains the first digit from each observation, builds a hypercube and uses it to count the first digits, extracts a dataset containing the distribution and, finally, computes the expected distribution and compares it to the observed distribution by taking the difference.

A Basic Introduction to Multidimensional Analysis Using Flow

This article presents a basic introduction to multi-dimensional analysis and analytics-oriented processing using Flow. It discusses datasets, measures, dimensions, and hypercubes; then it provides a step-by-step example of building a workflow to analyze some fictional A/B test data.

Introduction to Building Dashboards in Flow

Flow enables you to build dashboards containing a variety of elements including tables, charts, reports, and data summaries, among others. This post focuses on two methods you can use to build, populate, and update dashboards. I show how to add a new dashboard, then how to create and add chart result using one of the sample datasets provided. Next, I provide an in-depth discussion of adding workflow generated results to a dashboard.

Tables and Pivot Tables in Flow

In this post, we'll build a six-step workflow that produces Pivot Table and Table results. It shows how to load data, use expressions to derive time-period values from a date field, build a hypercube using those time-period values as dimensions and, finally, how to create and view pivot table and table results using the hypercube.

Grouped Reports in Flow

Here is the second in a series of posts focusing on building reports in Flow. A grouped report is an advanced report produced by Flow. Grouped Reports organize records into one or more nested groups where each group is is a collection of records with a common column data value. There are two basic methods you can employ to create grouped reports in Flow. The first is to add a Grouped Report action to a new or existing workflow. The second way is to open a hypercube within the Flow portal then click on the report icon Create Report button in the toolbar located at the top of the hypercube view. This post will cover the first method.

Tabular Reports in Flow

Flow enables you to build many types of reports, such as tabular, grouped, pivot tables, tables, and data summaries. This is the first in a series of posts focusing upon building reports in Flow. You can learn more about these different types of reports in the Flow online help. A tabular report is the most basic type of report you can build in Flow, it is organized in a multicolumn, multirow format, with each column corresponding to a column in a dataset.

Cognitive Computing in Flow

This post provides a hands on introduction to cognitive computing applications in Flow. It introduces the IBM Watson cognitive actions for unstructured text analytics a...