Cloud & Data Engineering

Analytics & Intelligence

Your data is in one place, but teams still wait weeks for answers and nobody quite trusts the dashboard. Flentas turns governed data into self-service BI, advanced analytics, and GenAI your teams can act on.

The Reality

When Getting Answers Takes Too Much Work

The data is finally in one place. Getting a decision out of it is still the hard part.

AI pilots hit a data wall

The model is ready, but the data isn't clean, trusted or accessible enough.

More analytics, more cloud cost

Usage grows, and so does the compute bill.

Dashboards go stale quickly

By the time a report is ready, the business question has already moved on.

Too much time goes into preparing data

Analysts spend more time cleaning and joining data than analyzing it.

Every team has its own numbers

Finance, sales and ops each report a different figure, and meetings turn into reconciliation.

Answers queue behind the analysts

A simple question waits weeks because only a handful of people can write the query.

Key Benefits

Insight the Business Can Trust and Reach on Its Own

A data platform on its own does not create insight. Analysts still lose close to 80% of their time preparing data instead of analysing it, almost 40% of teams name a lack of usable data as their top barrier to adopting AI, and nearly a third of GenAI projects are expected to be abandoned. The gap now is not storage — it is trusted, self-service intelligence people actually use.

  • Stop Arguing About Whose Metric Is Right

    Finance, operations, and marketing each define a metric their own way, and meetings turn into arguments about whose figure is correct. A governed metrics layer means a KPI means the same thing in every report.

  • Stop Queuing Behind the Analytics Team

    Business teams queue behind a small, overloaded analytics team, and by the time a manual export lands the moment has passed. Self-service BI and natural-language analytics let teams answer their own questions.

  • Get GenAI Pilots Out of the Sandbox

    The model is ready but the data behind it is not — quality, lineage, and access questions stall promising GenAI pilots before production. We ground GenAI in the same governed data your BI already trusts.

  • Scale Analytics Without the Bill Running Away

    Self-service adoption without cost visibility turns into a runaway compute bill. Analytics FinOps and right-sized compute keep scaling insight from becoming a budget problem.

Proof Points

Analytics That Scales Beyond the Dashboard

Lower analytics pipeline cost on a Flentas-built product-analytics platform
~40%
Applications unified into one self-service analytics and monitoring view
20+
Client retention across cloud and data engagements
96.5%
How It Works

Start With the Questions That Matter, Not a Rebuild

We begin with an assessment and sequence by value and feasibility, usually starting with a metric you already track and a business owner who wants the outcome. Prove value on one question, then extend the same pattern.

  1. 1

    Assess: Map the Decisions That Matter

    We map the decisions the business needs to make, the metrics behind them, and where trust in the numbers breaks down today.

  2. 2

    Build: Ship Governed Metrics and Self-Service

    We stand up governed metrics, the first dashboards or models, and self-service access for the teams that need answers.

  3. 3

    Operate: Run Analytics as a Managed Capability

    We run analytics as a managed capability, add use cases, and keep quality and cost under control as adoption grows.

Technology Stack

Technologies & Tools We Use

  • BI & Self-Service Analytics

    • Amazon QuickSight
    • Power BI
    • Tableau
    • Redash
    • Databricks SQL
    • embeddable analytics
  • Advanced Analytics & ML

    • Amazon SageMaker
    • Databricks Mosaic AI
    • forecasting & segmentation on curated, verified data
  • GenAI & Natural-Language Analytics

    • Databricks Genie
    • Amazon Q
    • Amazon Bedrock
    • natural-language-to-SQL and RAG on your own data
  • AWS-Native Analytics & AI

    • Athena
    • Redshift
    • Amazon Q
    • Bedrock
    • SageMaker
  • Governed Metrics & FinOps

    • Semantic layer
    • Unity Catalog governance
    • cost visibility and right-sized compute
  • Delivery Accelerators

    • ChangeSafe — Flentas' proprietary GenAI accelerator
    • Unity Catalog end-to-end governance
Case Studies

Where Analytics & Intelligence Makes a Difference

Retail & E-Commerce

Marketing, merchandising, and finance each run their own version of revenue — a governed metrics layer puts every team on one number before the next planning cycle.

Games Studio

Gaming & Mobile Apps

~40% Lower Analytics Pipeline Cost

Player and marketing events pile up faster than a small analytics team can turn into dashboards — a partitioned analytics lake and self-service BI let studios ship KPI views without a backlog.

Lending

Financial Services & Lending

20+ Applications Unified Into One View

Application and environment sprawl leaves no single view for operations or compliance — unifying everything into one self-service analytics layer restores visibility without adding headcount.

Any Team Piloting GenAI on Their Own Data

GenAI pilots ask a model to answer questions the underlying data was never governed to support — grounding natural-language analytics in a curated, lineage-tracked foundation is what gets a pilot into production.

“Every team had its own version of the numbers, and by the time an answer came back from analytics, the question had moved on. Flentas gave us a governed metrics layer and self-service dashboards our own teams could build from — and when we finally tried natural-language querying on top of it, people started using it the first week.”

VP of Product AnalyticsConsumer Mobile Gaming Platform

What's Next

Where This Fits in Your Journey

One engagement is one stage. Here is what usually comes before and after, so the next step is always clear.

Get Started

Turn Your Data Into Answers People Trust

Book an analytics assessment. We map the decisions your business needs to make, the metrics behind them, and where trust in the numbers breaks down today.