Analytic Labs Eclipse

Eclipse Cloud SaaS – The Next Generation of Data Intelligence

The last couple years in the retail industry have been a whirlwind of adapting and growing in many directions to find a “new normal.” But the omni-channel retail world has its own challenges, and gathering more data only means more opportunity if you can turn it into useable guidance. You can’t manage what you can’t measure; that’s where data analytics step up, and where Eclipse SaaS leaps ahead.

Business Intelligence Evolution

Our experience building robust measurement systems points to several distinct phases of business intelligence evolution that growing companies routinely fight through to turn their transactional data into actionable information. But there are alternatives. Compare the benefits and struggles of investing time in this traditional path or taking immediate advantage of cloud SaaS practical analytic reporting.

In the beginning: Start a company.

  • Use various programs for specific needs (like Google Analytics for marketing, QuickBooks for accounting, etc.).
  • Company operations are also varied and managed separately.
  • Buy or upgrade software or services as need arises, expanding data output.
  • Record output in a spreadsheet program (like Excel) to store, monitor operations, and track results.
  • Grow using those programs, and excellent business sense.

Soon, future planning and oversight requires connecting departments for information management. That’s a lot of work to understand but it seems worth it.

Phase 1: Invest in a big system (like an ERP).

  • Struggle to figure it out or make it work with necessary specialty programs.
    • Is there a bug, is it the setup, or are they incompatible?  Who knows! Managing a growing business doesn’t leave much time to become a data manager too.
  • Rely on the established Excel database to store data from recalcitrant programs and the big system together.
  • Keep growing, but the inefficiency that the ERP was meant to avoid is now creeping into operations and decision-making.

Something must be done to make sense of everything and connect information together in a useable format. In the meantime, operations still need increased management.

Phase 2: Add a second big system (both ERP and CRM).

  • Choose a system that promises “one place that handles all your reporting!” to avoid the same problems repeating.
  • Discover it doesn’t live up to its promise—it does not handle it all.
    • The systems aren’t compatible, or maybe it connects programs but doesn’t combine the right data fields.
  • Produce reports, but reports aren’t reliable for making informed plans.

After already investing in multiple systems, spending more money to make it work seems like the only solution. “Maybe we’re not doing Data Intelligence right.”—If heavier investment is needed anyway, why stop with just fixing reports?

Phase 3: Add visualization to make the investment worthwhile.

  • Find the software this time promises “can tie into most data sources you need!”
    • New program works with the big systems but requires expertise.
    • Original speciality programs aren’t providing data in the right format.
  • Hire a visualization analyst.
  • Invest in more systems and compatible programs.
    • Complexity continues to increase.
    • Keeping everything organized together in the initial setup is impossible.

Maybe a proper database to manage data would help? IT suggests a data warehouse. Boy, that sounds expensive.

Crossroads in Company Intelligence

This is the choice between lagging behind or leaping ahead, following or leading—between building technology or using it. The traditional solution means putting aside company growth while working to build an enterprise data warehouse. The effective alternative is to put your data to work through Eclipse’s cloud warehouse and meet growing business needs now.

Traditional data analytics

Traditional business intelligence departments have heavy requirements:

  • Servers
  • Data warehouse/databases licensing
  • Connectors
  • Visualization software
  • Experts to tie it all together
  • Time to build it all
    • The typical estimate of 8–10 months can take 1–2 years to function.
    • Time over the estimate increases already substantial capital investment.

And now your data, programs, and queries are all out of date. Time to start the whole process again…

Eclipse—intelligent data analytics

…Or skip the traditional solution. Gain the competitive advantage of speed without losing the versatility of guiding your own analytics.

As the next generation of data warehousing SaaS, Eclipse combines the best parts of bespoke and pre-boxed options:

  • Aggregates relevant data sources, regardless of format (including the “dark data” your company has been sitting on).
  • Demonstrates consistent sourcing, data interconnection, and customized queries without having to first “buy the box.”
  • Provides actionable reports and visualizations that answer your experience-informed questions to reveal business potential and address issues.
  • Includes managed analytics and data intelligence expertise to support your industry expertise.
  • Oversees flexible connections between data sources to optimize reporting information even as technologies change.

From Data Storage to Data Intelligence

Choosing the best route to growth is a unique position for every company. With your understanding of context and goals, your team is also uniquely placed to guide your reports and analytics. But you don’t need to build them to guide them—especially when innovative focus has turned to SaaS for “buy don’t build.”

To achieve your business goals, your business intelligence must advance. With the advantages of customizable Eclipse SaaS data analytics to find answers to your specific questions, your own company’s evolution doesn’t have to go through every phase of business intelligence growth.