Data to Decisions

Automation, Integration, Analytics, Reports & Dashboards

An End-to-End Data Analytics Walkthrough

Overview This blog post provides a worked example of an end-to-end automated business intelligence s

Overview

This blog post provides a worked example of an end-to-end automated business intelligence solution. This blog post demonstrates how to load data from different sources, join the data together, cleanse and correct data quality issues, compute hypercubes, and design a dashboard. I then demonstrate how to deploy the solution to the autonomous agent framework for continuous execution.

An End-to-End Data Analytics Walkthrough

Flow Crash Course - Part 8 - Data Visualization / HyperCube Visualization / Multi-dimensional Tables

This is the eighth blog post in our crash course series on Flow. In this blog post, I provide an int

Overview

This is the eighth blog post in our crash course series on Flow. In this blog post, I provide an introduction to HyperCube Visualizations and Multi-dimensional HyperCube Tables in the Flow Computing Framework.

Flow Crash Course - Part 8 - Data Visualizations and HyperCube Multi-dimensional Results

Flow Crash Course - Part 6 - HyperCube Computation

This is the sixth blog post in our crash course series on Flow. In this blog post, I provide an intr

Overview

This is the sixth blog post in our crash course series on Flow. In this blog post, I provide an introduction to HyperCube Computation in the Flow Computing Framework.

Flow Crash Course - Part 6 - HyperCube Computation

Flow Crash Course - Part 4 - Basic Data Summary Functions

This is the fourth blog post in our crash course series on Flow. In this blog post, I provide an int

This is the fourth blog post in our crash course series on Flow. In this blog post, I provide an introduction to Basic Data Summary Functions in the Flow Computing Framework.

Flow Crash Course - Part 4 - Basic Data Summary Functions

A Quick Introduction to the Five Types of Filters in Flow

In this blog post, I provide an introduction to the five filter actions in Flow. Filter actions are

Overview

In this blog post, I provide an introduction to the five filter actions in Flow. Filter actions are functions which select a specific subset of records from a designated data collection based on some target match criteria. This blog post introduces the different types of filters and provides a comprehensive worked video example demonstrating how to configure and implement these filters against a sample data collection. The filter actions are some of the most elementary and integral operations in the Flow computing framework. Mastering the different types of filters is key to data processing, data analytics, and business intelligence workflow design.

A Quick Introduction to the Five Types of Filters in Flow

 

 

Analyze Blank or Missing Data Values Using Flow Analytics

Overveiw In this blog post, I provide a worked example demonstrating how to perform an analysis of b

Overview

In this blog post, I provide a worked example demonstrating how to perform an analysis of blanks on a target dataset. When analyzing data a typical first step is to get an understanding of where there are missing values. Identifying where there are missing values in your data can help you make more informed decisions about your analysis approach.

How to Analyze Blank or Missing Data Values Using Flow Analytics

 

 

Perform a Word Count Analysis with Flow Flow Analytics

Overview This article demonstrates how to perform a word count analysis in Flow. In this blog post,

Overview

This article demonstrates how to perform a word count analysis in Flow. In this blog post, I provide a worked example showing how to take in unstructured natural language data and compute a unigram language model against that data. The result of the language analysis returns a new profile dataset which holds each unique token present in our natural text and the count of times each word occurred. This blog post teaches a quick one-step technique for doing an initial exploratory analysis of natural text data.

How to Perform a Word Count Analysis with Flow Flow Analytics

 

 

How to Denormalize (Join) Data Using Flow Analytics

Overview This blog post demonstrates how to configure the denormalize function in order to join disc

Overview

This blog post demonstrates how to configure the denormalize function in order to join disconnected data sets together. A worked example is provided which shows how to import and merge various delimited files. The denormalize action is used to join the data from the separate files together in order to consolidate them into a single set for analysis. Once the data is joined, we learn how to use hypercubes to aggregate and summarize the data.

How to Denormalize (Join) Data Using 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

 

 

 

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