Initial Consultation & Strategic Objectives

"Business defines needs; needs imply goals, goals drive objectives" :  Sounds simple; but every executive knows that the secret sauce is not in a thought framework, but in how well it’s applied.

“Effectiveness” in this modality is actually about how well needs are articulated; how well goals are aligned to needs; how relevant the objectives are to achieving those goals.  This is especially true with data-centric projects and efforts.  Data has to be identified as pertinent to objectives but it must also be managed and shaped to satisfy goals.

INFORMODAL works with you and your team to define goals and translate those into firm and concrete objectives,
in the process defining:

• Business Process Definition & Work Flow Charting
• Reporting Requirements
• Analytics goals

Monitoring, Measurement and Modeling Definitions

Do you have a need for real-time monitoring?  Call centers, scientific research, stock market analytics, these endeavors all live and die by the accuracy and clarity of data; we have helped companies like yours define, enable and /or build out near-real-time systems for managing employees, monitoring resources and events, and aggregating IOT/device/control/Appliance data from thousands of remote sites and devices.

The “Internet Of Things” is an explosion in progress; bridging vast and hugely partitioned data with business operations is an evolving art and science and industry practice.  As this phenomenon grows, INFORModal continues to evolve our practices, enriching your data collection and integration efforts with the experience gained from dozens of others in your industry and outside it.

We’ll help you build a layer of meaning and accessibility over the incoming raw data, so it may be dimensionalized, metricized and integrated to bring meaning and value to your organization.

Data Extraction, Transformation and Loading

Extraction, Transformation and Loading (ETL) are the steps taken to bring data “in” from a source, and integrate it into a larger model.  This effort is itself critical to success in any data project; so much so that ETL developers and managers tend to be specialists.

Practicing the art and science of moving data from where its generated to where it can be correlated to a larger context has become a whole field unto itself, and here at INFORModal we respect the depth and breadth of these efforts.  As such, we maintain a base of talent second to none, bringing ETL experts to bear whenever their specific talents are required.

There’s also a lot more to ETL than just moving data from here to there and integrating it well; the real difference between “good” ETL and “bad” ETL is in its expression of:

• Clean and modern coding practices (reusability, modularity, etc.)
• Fault tolerance / job recoverability
• Source values maintenance
• Accountability / audit-ability

Each of these virtues should be built into any process made to perform ETL; they conspire to make a system that requires little to no manual input, and very quick resolvability of errors, within any modality of concern:  data, metadata, data at rest, data in motion.

Data Warehousing

Do you need to build a reporting system for your internal operations?  
Do you want to offer data reporting services to your prospects as an add-on to remain competitive and close sales? 
Are you thinking about a COTS solution for reporting?

 
You’ll likely need to consider a Data Warehouse as a systematic approach to organizing your data and as a practice to get all the resources into one place…but the benefits of a Data Warehouse extend beyond just making life easier for a report author or reporting off-the-shelf “system”.

A Data Warehouse is also an opportunity to apply business logic and make the results of that logic available as readable, browse-able, reportable data.  Conclusions become available for reporting alongside the source data that generated them.

“What-ifs” may also be assembled in a Data Warehouse to model and represent results from each of multiple approaches to a challenge.

Data Warehouses also drive strict and sharp definitions around the data itself; by virtue of building out a Data Warehouse, organizations leverage the knowledge gained in building it; no confusion is left as to approach, or source, or query once a Data Warehouse is completed.

INFORModal has defined and built hundreds of successful Data Warehouses; some were the entire mandate for helping a client.  Others are built to support a larger system of reporting and analytics that we take on as a next natural step.

Reporting & Visualization

OK:  we’ve defined our need, we’ve quantified our drivers, we’ve assembled a Data Warehouse.  In doing so, we’ve defined business entities, charted practices, built a data dictionary, clarified relationships and uncovered answers to age-old mysteries about the business…it’s time for some results!

Reports/Analytics is where most conversations about data start.  All the underlying organizational challenges can’t be ignored; these are prerequisite to building results inexpensively, effectively and coherently in a manageably consistent way.

Once we get here, though, our minds can open to a panacea of possibilities.  The simplest reports are just enumerations of facts, dimensions and metrics.  Some of the most valuable reports elucidate facts, figures and relationships by making them obvious to your visual cortex – especially when a look at the source data would not easily bring similar insight.

At INFORModal we believe that connecting two computers – your reporting system and your brain – can produce immediate and powerful explanatory power simply unavailable to any other method of illustration or persuasion.

“Speaking” to the visual mind is better defined as a talent than as a technical skill.  While it takes technical acumen to build out an environment and report that accurately reports values, it takes a keen eye and an artistic bent to deliver intuition.

INFORModal ca n deliver all your reporting needs to a simple, static spec, and we do so often.

INFORModal can also apply a unique means of delivering a multiplicity of report layouts, arrangements, approaches and images to see which best fit your messaging, your targeted cultures, and your objectives.

Analytics & Forecasting

Analytics:  asking questions, answering questions.  Methods vary widely from simple one pass queries to deeply complex approaches and operations.

Forecasting:  anticipation of the future, based on knowledge of the past.  This practice ranges from simple signal processing through highly multi-variate and event-aware predictions.

Data Mining:  the search for known and unknown trends and relationships; a search for causality.  This practice is usually associated with higher mathematics than the typical Analytics effort; generally applies as a meme to examine internal practices (pricing, inventory levels, etc.) and their relationships to external effects (sales volumes, retention rates, etc.).

At INFORModal we’re rarely called upon to perform only Analytics work.  Our approach yields greater value for those whom have built their data systems with our help.

This is because we consider Reporting, Analytics and Forecasting to be our ultimate goals, from our business perspective, in delivering value to you.  The best built Data Warehouse in the known Universe is useless unless we can extract data and meaning from it.

By building our (yours) data systems in anticipation of Analytics, we “organically” build in elements and data points and a foundation for Analysis into our mindset as a design principle; this translates into a highly usable product, in practice.