SAP Analytics Cloud and Datasphere

Reports leadership trusts, data modelled once, and a month-end that stops breaking, from consultants who have done SAP analytics for decades.

Book A Consultation
GlueData
Sanlam
Wastepro
FINN
Southco
OSIsoft
Sports Basement
SALT Analytics
AME Africa
Lock & Stern
ClearOn
WEG
Savantis
Sanquin
Hua Hai Pharma
Rumpke
GlueData
Sanlam
Wastepro
FINN
Southco
OSIsoft
Sports Basement
SALT Analytics
AME Africa
Lock & Stern
ClearOn
WEG
Savantis
Sanquin
Hua Hai Pharma
Rumpke

What we do

  1. We build the reports leadership actually uses.

    SAP Analytics Cloud stories and dashboards for executives, controllers and analysts, built from what they need to decide, checked against the source and changed as the questions change.

  2. We model the data once, properly.

    Data models in SAP Datasphere with hierarchies, currency conversion and period logic defined in one place, so every report carries the same definition of the metric.

  3. We make month-end boring.

    Data loads, schedules and jobs checked before finance starts its day, change frozen during close windows, and the P&L, balance sheet and cash flow models reconciled to the source ledger.

  4. We make the slow report fast.

    Views, loads and federation tuned so a dashboard opens in seconds and the overnight schedule finishes before the morning, instead of everything replicated just in case.

  5. We fill the gaps the product leaves.

    Where SAP Analytics Cloud cannot do what the business needs, such as scheduled reports in Excel rather than PDF, we build the workaround and keep it running.

  6. We lay the foundation AI can use.

    Governed, trusted data with controls and security built in, so analytics and AI use cases build on numbers finance already trusts.

What that looks like in practice

The scheduled report that had to be Excel

Leadership wanted the scheduled reports as spreadsheets so they could work on the figures, and the product only sends PDFs. We built a conversion that turns the scheduled PDF output into formatted Excel with every threshold intact, and added a plain-language summary of what changed, by how much, and where to look next.

The data platform that had to be rebuilt

A Datasphere implementation had been built in a hurry and nobody trusted it: models that disagreed, loads that failed, reports that opened late. We rebuilt the models on an agreed set of definitions, stabilised the schedules and tuned the slow views. Six months later the numbers were trusted enough to close on.

The close that stopped breaking

Every month-end something in the reporting chain broke, and finance found out at the worst time. We put change control around the financial models, froze risky releases during the close window, and reconciled the models to the ledger as part of the schedule. Finance now finds no discrepancies, because the data team already has.

Where SAP analytics goes wrong

The same four things, in almost every landscape we inherit.

  • Dashboards built straight on raw tables, so every report carries its own logic for hierarchies, currencies and periods.
  • Two reports, two different P&L numbers, and no agreed definition of the metric.
  • Everything federated or replicated just in case, so month-end crawls.
  • Reporting left for last, and every department back in its own spreadsheet.

What we work in

Every product, model and practice our analytics consultants use, by layer.

SAP Analytics Cloud

  • Stories and dashboards
  • Planning and versions
  • Scheduling and distribution
  • SAC add-in for Microsoft Excel
  • Data actions and calculations
  • Roles and data access

SAP Datasphere

  • Data models, views and spaces
  • Replication and federation
  • Hierarchies and currency conversion
  • Task chains and schedules
  • Performance tuning
  • Data integration from S/4HANA and BW

Finance models

  • P&L, balance sheet and cash flow
  • Budget and forecast versions
  • Reconciliation to the ledger
  • Period and version logic
  • Headcount and statistical key figures

Wider data stack

  • SAP S/4HANA and BW/4HANA
  • SAP Business Data Cloud
  • SAP HANA Cloud
  • Snowflake and Microsoft Azure
  • dbt and Medallion architecture
  • Power BI

Operations

  • Job and schedule monitoring
  • Change control at month-end
  • Testing before transport
  • Performance reviews
  • Documentation and handover

Signs you need us

  • Two reports give two numbers for the same KPI.
  • Month-end waits for a data load that failed overnight.
  • The dashboard takes a minute to open.
  • Leadership still works from spreadsheets exported by hand.
Talk to an analytics consultant

You can find us here

We have a strong global presence, marking our commitment to delivering tech excellence in key markets worldwide.

Colorado
14133 Downing Street Brighton,
Colorado 80602
Contact us
Cape Town
Regus Business Center, 1st Floor,
Willowbridge, Cape Town
Contact us
Haarlem
Frame Offices B.V.,
Haarlem, Netherlands
Contact us

AI on numbers finance already trusts

The ETZ AI Platform answers plain-language questions against your governed data models and explains what changed and why, with SAP-grade authorisation and an audit trail on every action.

See the ETZ AI Platform Book a consultation
  • Runs in your own SAP BTP subaccount. SAP data never transits ETZ.
  • Your SAP authorisations decide what it may see and do, not the AI.
  • Every action lands on an append-only audit record.
Available on the SAP Store (opens in a new tab)