Data to Decisions

Automation, Integration, Analytics, Reports & Dashboards

Building Grouped Reports with Flow Analytics

Here is the second in a series of posts focusing on building reports in Flow. A grouped report is an

Overview

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.

Building Grouped Reports with Flow Analytics

 

 

Use Flow Analytics + Artificial Intelligence to Analyze the News

Overview In this blog post, I provide a worked example demonstrating how to design a workflow which

Overview

In this blog post, I provide a worked example demonstrating how to design a workflow which extracts and analyzes cryptocurrency news articles using artificial intelligence. I explain how to use the HTML integration interface to extract links for all top news stories from a target website into data. I show how to use generic expressions to transform and clean the raw links, preparing them for processing. Flow is used to loop through each of the structured links and invoke the built-in Watson artificial intelligence functions to perform advanced cognitive analytics against the text of each news article. Flow collects the results of the cognitive analysis and compiles an aggregate dataset of sentiments, emotions, concepts, topics, keywords, and named entities for all of the supplied articles. I finish the example by showing how to compute hypercubes against the cognitive output to summarize the results and generate various multidimensional views.

How to Use Flow + Artificial Intelligence to Analyze the News

 

 

 

Use Flow and Watson AI for SEO Keyword Research

This article demonstrates how to use artificial intelligence in order to perform keyword research fo

Overview

This article demonstrates how to use artificial intelligence in order to perform keyword research for search engine optimization. Watson cognitive actions are leveraged in order to decompose keywords from competitor websites. Keywords are compiled into a dataset in order to provide better insight into potential SEO strategy.

How To Use Flow and Watson AI for SEO Keyword Research

 

 

How to Perform a Cognitive Keyword Extraction On Unstructured Text Using Flow Analytics

Overview This post demonstrates how to perform a cognitive keyword extraction against natural langua

Overview

This post demonstrates how to perform a cognitive keyword extraction against natural language text data in Flow. In this worked example I show how to use the artificial intelligence actions to process unstructured text values. The artificial intelligence actions are used to deduce all-important keywords, analyze sentiment towards those keywords, and compute emotion distribution scores for each string extracted from the natural language text. The concepts examined in this post teach a powerful technique which can be used to develop advanced cognitive workflows against any data source.

How to Perform a Cognitive Keyword Extraction On Unstructured Text Using Flow Analytics

 

 

Doing Data Quality with Flow Analytics

In this article, I provide an introduction to measuring and evaluating data quality using Flow. I br

Overview

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 Analytics using some sample name and address data. 

Doing Data Quality with Flow Analytics

 

 

Perform a Benford Analysis Using Flow Analytics

Overview n this post, we build a reusable eight-step Flow that performs a basic Benford's Analysis o

Overview

n 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.

Perform a Benford's Analysis Using Flow Analytics

An Introduction to Building Dashboards in Flow Analytics

Overview Flow enables you to build dashboards containing a variety of elements including tables, cha

Overview

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.

An Introduction to Building Dashboards in Flow Analytics

Building Tables and Pivot Tables in Flow Analytics

Overview In this post, we'll build a six-step workflow that produces Pivot Table and Table results.

Overview

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.

Building Tables and Pivot Tables in Flow Analytics

A Basic Introduction to Multidimensional Analysis Using Flow

Overview This article presents a basic introduction to multi-dimensional analysis and analytics-orie

Overview

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

An Introduction to Multidimensional Analysis

Building Tabular Reports in Flow Analytics

Building Tabular Reports in Flow Analytics Flow enables you to build many types of reports, such as

Overview

Flow enables you to build many types of reports, such as tabular, grouped, pivot tables, tables, and data summaries. Here 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.

There are two basic methods you can employ to create tabular reports in Flow. The first is to add a Tabular Report action to a new or existing workflow. The second way is to open a dataset within the Flow portal then click on the report icon Create Report button in the toolbar located at the top of the dataset view. This post will cover the first method.

Building Tabular Reports in Flow Analytics