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A Brief Explanation
Flow
A Brief Explanation
The field of Data Science presents many opportunities and obstacles in terms of
gathering insight from Big Data. As grand as the opportunities can be, the hurdles can
be just as challenging. Flow is a solution that overcomes these obstacles and allows
your company to reap the insight of Big Data.
Key Hurdles to better data use​:
● Data Overload
● Data Quality
● Knowledge Required
The Solution
Flow allows your organization to overcome all three hurdles in one environment.
Flow's Generic Data is capable of scaling to whatever size is necessary through
our intuitive and seamless distributed Agent Architecture.
Generic Data is ready to accept data from a plethora of structured and
unstructured data sources, so the quality of your data is guaranteed to be consistent
across disparate systems.
Flow is an incredibly simple software to understand and master. We have
abstracted away all the foreign concepts that have made data science a foreign
language. By encompassing all the features of data science programming languages
into an intuitive, simple environment, we have made Data Science approachable and
teachable.
1
A Brief Explanation
Summary​:
Flow is a Hypercube-based data science engine, used to design workflows which
automate advanced tasks.
These tasks include:
• Creating intelligent communication streams across systems
• Performing large scale hypercube computation
• Automating advanced decision logic
• Processing monitoring, anomaly detection and control
• Report generation and automated distribution logic
• Data mining many disconnected sources
• Distributed parallel processing of data sets
2
A Brief Explanation
Delivering Growth
From a Chief Marketing Officer's point of view, the objective of any data
analytics platform is to be able to deliver growth to your company. This translates into
optimizing pricing, marketing efforts, and strategies. The solution for an optimized
marketing campaign lies in your understanding of your customer. Data will help you
understand customers better.
Flow offers your company to tap into the unstructured world of Social Media and
hear your customer's sentiments directly. This will lead to an optimized marketing
strategy and optimized pricing scheme.
Controlling Costs
From a Chief Operating Officer's standpoint, a data architecture must be able to
analyze internal expenses in an effort to control costs. This encompasses analyzing
supply chains, operational efficiency, and market demands due to external events.
Flow will accept any databases representing these expenses and allow your company
to efficiently manage and optimize the costs. This will lead to an improved operational
efficiency, inventory management, and resource usage.
Risk Management
From a Chief Financial Officer’s vantage point, an all encompassing data
solution needs to be able to portray the knowledge gathered from data in a simple, yet
insightful manner. This means being able to spot the cost efficiencies, portray the
visibility of markets, and highlight financial risks right from one consolidated location.
Flow's Dashboards offer multidimensional representations of data to spot correlations,
a myriad of graphs and charts to spot trends, and simplified summary items to detect
anomalies.
A Dashboard is a an encompassing view into an organization's risks and
operations. This will lead to improved financial risk management, improved corporate
meetings and reports, and an improved ability to spot cost inefficiencies.
3
A Brief Explanation
An Overview​:
Flow is a new way to program
• Flow represents a new design paradigm called "Configure-not-Code". Flow
removes absolutely all coding needed from the data science process,​ leading to
unmatched efficiency​.
• The Flow developer interacts with higher level actions. These actions embody
the fundamental laws of computing.
• Flow actions are sequenced based on the logic of a process.
• Through sets of joins, unions, loops, jumps, conditionals, regular expressions,
stack expressions, hypercubes, web protocols, variable instantiations, dynamic
parameters, bidirectional data access and generic expressions,​ Flows can be
designed to execute virtually any set of rules​.
• The Flow developer deploys Flows to agents. Agents can be​ distributed across
many machine​s.
• Flows can execute other remote, local, and cloud based Flows
• Flow developers can​ rapidly create systems of systems
• Flow also consists of a cloud environment. Flow Cloud provides a repository for
Data, Flows, and Results.
• Creation of Result elements is configured into the Flow logic. This allows Result
elements to be updated on a scheduled basis
• Data, Flows, and Results are all sharable via Flow Cloud. This enables Flow
developers to communicate and collaborate,​ which leads to increased output​.
This also allows​ business-orientated users to easily interact with the output.
• Hypercubes are tapped into to draw dynamic drill through views of the high
dimensional data structure, consolidating desired information in a simple and
powerful way
4
A Brief Explanation
Our Purpose​:
Flow was built with nothing but a passion for the industry and a desire to
fundamentally advance the field of computing.
We are advancing the platform every day, expanding in all possible areas of data
science.
Flow is a complete data architecture that facilities all data analytic tasks in one
simple environment​.
Four years later,
We present Flow 1.0
For further inquiry, please contact:
Hypercube Artificial Intelligence Division
Andrew McLaughlin, Lead Developer
andrew.mclaughlin@​4DIQ​.com
484.862.7811
Jeremy Villar, Marketing
jeremy.villar@​4DIQ​.com
860.877.4277
Anthony Parziale, Developer
anthony.parziale@​4DIQ​.com
860.605.7096
5
A Brief Explanation
Features​:
(For an extensive list of features, please review the Executive White Papers included)
Importing/Exporting data from/to​:
- Local Files
- Databases
- Web APIs
- CRMs
- Social Media
- Analytics Platforms
- to/from FTP sites
Data Point Management
- Add/Remove Data Points
- Indexing
- Converting Data Point types
Database Management
- Sort, Slice, Append, Deduplicate, Denormalize
- Filters/Lookups
- Data Point Filter
- Contains Text
- Index based filter
- Top N Filter
- Random Sample Filter
- Add/Remove Data Sets
Workflow Execution
- Jumps (Conditional Jumps(if statement), For-Each Loops)
- Delays
- Detect Different Data function (decisions based on if the database has been updated)
- Execute Flows Local or Remotely
- Run External Programs(Flow can run any external program through the cmd prompt)
Email Actions
- Automatically send emails based on desired outcomes
Summary Functions
- Frequency Distribution
- Data Description Function
Data Visualization/ Dashboard Creation
- Create interactive and dynamic Graphs
- Group graphs, charts, tables, summary items into one Dashboard for reporting
6

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Flow-ABriefExplanation

  • 1. A Brief Explanation Flow A Brief Explanation The field of Data Science presents many opportunities and obstacles in terms of gathering insight from Big Data. As grand as the opportunities can be, the hurdles can be just as challenging. Flow is a solution that overcomes these obstacles and allows your company to reap the insight of Big Data. Key Hurdles to better data use​: ● Data Overload ● Data Quality ● Knowledge Required The Solution Flow allows your organization to overcome all three hurdles in one environment. Flow's Generic Data is capable of scaling to whatever size is necessary through our intuitive and seamless distributed Agent Architecture. Generic Data is ready to accept data from a plethora of structured and unstructured data sources, so the quality of your data is guaranteed to be consistent across disparate systems. Flow is an incredibly simple software to understand and master. We have abstracted away all the foreign concepts that have made data science a foreign language. By encompassing all the features of data science programming languages into an intuitive, simple environment, we have made Data Science approachable and teachable. 1
  • 2. A Brief Explanation Summary​: Flow is a Hypercube-based data science engine, used to design workflows which automate advanced tasks. These tasks include: • Creating intelligent communication streams across systems • Performing large scale hypercube computation • Automating advanced decision logic • Processing monitoring, anomaly detection and control • Report generation and automated distribution logic • Data mining many disconnected sources • Distributed parallel processing of data sets 2
  • 3. A Brief Explanation Delivering Growth From a Chief Marketing Officer's point of view, the objective of any data analytics platform is to be able to deliver growth to your company. This translates into optimizing pricing, marketing efforts, and strategies. The solution for an optimized marketing campaign lies in your understanding of your customer. Data will help you understand customers better. Flow offers your company to tap into the unstructured world of Social Media and hear your customer's sentiments directly. This will lead to an optimized marketing strategy and optimized pricing scheme. Controlling Costs From a Chief Operating Officer's standpoint, a data architecture must be able to analyze internal expenses in an effort to control costs. This encompasses analyzing supply chains, operational efficiency, and market demands due to external events. Flow will accept any databases representing these expenses and allow your company to efficiently manage and optimize the costs. This will lead to an improved operational efficiency, inventory management, and resource usage. Risk Management From a Chief Financial Officer’s vantage point, an all encompassing data solution needs to be able to portray the knowledge gathered from data in a simple, yet insightful manner. This means being able to spot the cost efficiencies, portray the visibility of markets, and highlight financial risks right from one consolidated location. Flow's Dashboards offer multidimensional representations of data to spot correlations, a myriad of graphs and charts to spot trends, and simplified summary items to detect anomalies. A Dashboard is a an encompassing view into an organization's risks and operations. This will lead to improved financial risk management, improved corporate meetings and reports, and an improved ability to spot cost inefficiencies. 3
  • 4. A Brief Explanation An Overview​: Flow is a new way to program • Flow represents a new design paradigm called "Configure-not-Code". Flow removes absolutely all coding needed from the data science process,​ leading to unmatched efficiency​. • The Flow developer interacts with higher level actions. These actions embody the fundamental laws of computing. • Flow actions are sequenced based on the logic of a process. • Through sets of joins, unions, loops, jumps, conditionals, regular expressions, stack expressions, hypercubes, web protocols, variable instantiations, dynamic parameters, bidirectional data access and generic expressions,​ Flows can be designed to execute virtually any set of rules​. • The Flow developer deploys Flows to agents. Agents can be​ distributed across many machine​s. • Flows can execute other remote, local, and cloud based Flows • Flow developers can​ rapidly create systems of systems • Flow also consists of a cloud environment. Flow Cloud provides a repository for Data, Flows, and Results. • Creation of Result elements is configured into the Flow logic. This allows Result elements to be updated on a scheduled basis • Data, Flows, and Results are all sharable via Flow Cloud. This enables Flow developers to communicate and collaborate,​ which leads to increased output​. This also allows​ business-orientated users to easily interact with the output. • Hypercubes are tapped into to draw dynamic drill through views of the high dimensional data structure, consolidating desired information in a simple and powerful way 4
  • 5. A Brief Explanation Our Purpose​: Flow was built with nothing but a passion for the industry and a desire to fundamentally advance the field of computing. We are advancing the platform every day, expanding in all possible areas of data science. Flow is a complete data architecture that facilities all data analytic tasks in one simple environment​. Four years later, We present Flow 1.0 For further inquiry, please contact: Hypercube Artificial Intelligence Division Andrew McLaughlin, Lead Developer andrew.mclaughlin@​4DIQ​.com 484.862.7811 Jeremy Villar, Marketing jeremy.villar@​4DIQ​.com 860.877.4277 Anthony Parziale, Developer anthony.parziale@​4DIQ​.com 860.605.7096 5
  • 6. A Brief Explanation Features​: (For an extensive list of features, please review the Executive White Papers included) Importing/Exporting data from/to​: - Local Files - Databases - Web APIs - CRMs - Social Media - Analytics Platforms - to/from FTP sites Data Point Management - Add/Remove Data Points - Indexing - Converting Data Point types Database Management - Sort, Slice, Append, Deduplicate, Denormalize - Filters/Lookups - Data Point Filter - Contains Text - Index based filter - Top N Filter - Random Sample Filter - Add/Remove Data Sets Workflow Execution - Jumps (Conditional Jumps(if statement), For-Each Loops) - Delays - Detect Different Data function (decisions based on if the database has been updated) - Execute Flows Local or Remotely - Run External Programs(Flow can run any external program through the cmd prompt) Email Actions - Automatically send emails based on desired outcomes Summary Functions - Frequency Distribution - Data Description Function Data Visualization/ Dashboard Creation - Create interactive and dynamic Graphs - Group graphs, charts, tables, summary items into one Dashboard for reporting 6