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Mobiloitte upgrades the full BI stack from the semantic metrics layer for DBT and governed data models to causal and predictive intelligence and real-time dashboards. Every decision becomes clear, repeatable, and tied to business outcomes.
Replace black-box metrics with a warehouse-first BI platform using dbt models and a shared semantic layer.
Kafka, Flink, and Spark feed live dashboards, alerts, and decision engines.
Move beyond correlation with causal inference for marketing lift, uplift modelling, and disciplined tests.
ARIMA/Prophet, GBMs, and DL forecasts with confidence bands and simple explanations great for predictive forecasting for demand planning.
Turn analytics into safe, policy-based actions that can trigger changes automatically.
Semantic layers and curated templates let teams explore without breaking metrics.
One source of truth with versioned metrics, lineage, and documented assumptions.
FinOps dashboards, partitioning, compaction, vectorisation, and caching.
Narratives, anomaly explanations, and grounded NLQ for faster insights. .
Freshness checks, drift detection, anomaly alerts, and SLAs for reliable decisions.
Explainable AI dashboards for executives, model cards, and audit logs.
SLAs, runbooks, governance reviews, and training for PMs, finance, and leaders.
Many teams face dashboards that disagree, metrics that drift, and SQL no one can defend. Mobiloitte fixes this with a warehouse/lakehouse core, a semantic metrics layer, and governed pipelines. Causal and predictive analytics sit on top, along with decision automation. Every metric is versioned, tested, and visible, so BI becomes easy to audit and safe to grow.
Well coded dbt tests, CI/CD, and visibility across analytics and models.
Responsive Embedded pods partner with finance, product, ops, and marketing..
Fast growing Scales with teams, events, SKUs, and markets.
Multipurpose Dashboards, ML, LLMs, and activation share one foundation.
Mobiloitte Aligns KPI Trees, Metric Dictionaries, Semantic Layers, and Governance So No One Argues Over “Which Dashboard Is Right.” Ownership, SLAs, Cost Policies, and Compliance Are Set to Pass Internal and External Audits.
KPI tree and semantic metric catalog
Data/metric contracts, lineage, and access rules
Warehouse/lakehouse architecture and modeling standards
Cost, SLA, and FinOps framework
Governance policies and documentation
Mobiloitte Delivers DBT Modelling, Streaming Pipelines, Operational Dashboards, Forecasting, Causal Inference, and Decision Automation. LLMs Add Narratives and NLQ With Grounding and Evals.
dbt models + semantic metrics layer + lineage
Kafka/Flink/Spark streaming → instant dashboards and actions
Causal inference, uplift modeling, forecasting, and scenario tools
Decision engines with policy enforcement (alerts → actions)
Narrative BI and NLQ with guardrails and evaluations
Mobiloitte Runs and Improves Analytics With Retraining, Data Quality Checks, CI/CD for BI Codes, FinOps, and Practical Training for Non-Technical Teams.
Model registry, retraining jobs, and drift/latency alerts
Data observability (freshness, schema, anomalies)
FinOps dashboards, budgets, and optimization
Cross-functional enablement and playbooks
24/7 SLAs and joint roadmap planning
Agree on metrics, KPIs, governance, and Architecture. Pick a stack based on cost, control, and integrations.
Ship pipelines, dbt models, dashboards, forecasting/causal analytics, and decision engines with CI/CD and observability.
Retrain models safely, tune costs, and automate actions with clear guardrails and audit logs.
Snowflake • BigQuery • Redshift • Databricks • Delta/Iceberg/Hudi • dbt • Airflow/Prefect • Kafka/Flink/Spark • Looker • Power BI • Mode • Superset • Cube/Transform • MLflow • W&B • LangChain/LlamaIndex • Feast • ClickHouse • DuckDB
Compliance is built in: SOC2/GDPR/HIPAA/PCI alignment, access control, masking, consent awareness, lineage, model cards, policy automation, and audit logs. XAI views make it simple to explain why models and metrics acted the way they did.
Mobiloitte defines metrics once in code with tests and version control. All dashboards, notebooks, models, and activations pull from the same rules. Finance, product, and marketing see the same numbers, and changes roll out everywhere at once.
Correlation shows relationships; causality shows impact. Causal models and uplift analysis reveal which actions truly move KPIs. This helps teams invest in strategies that create real lift, not just nice-looking charts.
Yes. Kafka/Flink/Spark streams power minute-level views, anomaly alerts, and safe automatic actions. Observability, SLAs, and playbooks keep real-time reliable
Yes. Grounded NLQ and narratives speed insight, while guardrails, evaluations, and PII controls protect accuracy and privacy. Cost and latency are monitored like any production service.
Clear models (Prophet/ARIMA) and advanced ML/DL are paired with confidence bands, backtests, and plain-language explanations. Results tie to business outcomes like inventory, staffing, and cash-flow risk.
Analytics can trigger policy-based actions, discounts, budget shifts, throttles, or alerts with human override. Every action is logged, understandable, and reversible.
A FinOps framework tracks costs by team and workload. Heavy queries are redesigned; partitioning, caching, and vectorisation keep spending in check. Storage and compute choices follow growth needs, not vendor hype.
IYes. Mobiloitte centralises metrics into a catalogue and semantic layer, removes duplicates, and migrates logic to tested dbt models. CI/CD manages changes without stopping the business.
Yes. Open-source stacks can run on-prem or in a private cloud with full control of data, models, and policies without losing modern features.
Role-based dashboards, a semantic layer, and safe explore surfaces give speed without metric drift. Training covers interpretation, experimentation, and governance.
A governed MVP (semantic layer + core dashboards) usually ships in 4–8 weeks. Streaming, forecasting, causal inference, and automation follow in 8–12+ weeks, released in stages for quick wins.
Mobiloitte tracks adoption, decision cycle time, data trust scores, alert quality, experiment throughput, and revenue/efficiency gains from automated decisions. BI is built to pay for itself and the team shows how.
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Dashboards alone are not enough. Mobiloitte delivers an analytics backbone that moves KPIs, not just reports them, with streaming, predictive, explainable, and governed workflows.