The Cost of Leaving Data Work Disconnected

Most data teams work across disconnected tools, and much of their week goes to manual cleanup, discovery, and report maintenance instead of insight. When that fragmented work continues, the cost builds quietly and shows up across the business.

Untrustworthy Decisions

When teams can't trust the numbers, every decision carries hidden risk, and leaders hesitate to act on the insight in front of them.

Wasted Effort on Unused Reports

Hundreds of redundant, outdated reports consume engineering hours while no one has the time or visibility to decide which to retire.

Rising Cloud Costs

Unused storage, oversized warehouses, and inefficient queries inflate cloud bills with little visibility into where the money goes.

Slower Time to Insight

Fragmented, manual processes delay answers, and opportunities pass to faster-moving competitors.

Growing Technical Debt

Disconnected tools and tribal knowledge pile up and make every future change more difficult, risky, and expensive.

One Workspace for Your Entire Data Lifecycle

Are you accountable for whether or not the business can trust its data or for a cloud bill that keeps growing? MPH for Data distills 20 years of enterprise data transformation experience into repeatable, AI-powered accelerators. Your team sees what to fix, consolidate, and modernize in one place and then takes action from the same platform.

Watch a two-minute overview of MPH for Data.

Built for Your Existing Stack

MPH for Data layers intelligence on top of the platforms you already run, such as Snowflake and Databricks, which protects prior investments.

No-to-Low-Code Accelerators

Proven accelerators compress work that once took specialists weeks, and teams reach value twice as fast as they would with traditional manual delivery.

Baselines in Hours

Your leaders receive measurable baselines and prioritized recommendations in hours instead of months.

People in Control

AI agents never make changes silently. Low-confidence outputs go to a person for review, cutting manual effort while your team keeps control.

Three Steps to a Clear Starting Point

Your path to MPH for Data starts with a conversation about your environment and ends with an objective view of where you stand.

1

Talk to a data expert.

Book a personalized walkthrough with our team. The session focuses on the accelerators most relevant to your environment and priorities and leaves room for your questions throughout.

2

See your scenarios.

The demo runs on the platforms you already use, such as Snowflake and Databricks. You see exactly how each accelerator would work with your own data.

3

Leave with a baseline.

The maturity assessment gives you an objective, benchmarked view of where you stand and which priorities return value fastest.

Talk to a data expert

How MPH for Data Helps You Move Faster

The DASH framework describes how your team moves from first analysis to confident action. AI-powered accelerators support every stage of the data lifecycle.

D

Discover

Surface gaps, overspend, duplicated effort, and more with AI-powered analyses.

A

Authenticate

Confirm that your data is trustworthy in every context where it's used.

S

Synthesize

Bring your entire data ecosystem together in one intelligent platform.

H

Harness

Act on insight and make approved changes with the click of a button.

A Growing Set of AI-Powered Accelerators

Every accelerator runs in the same shared workspace with a single sign-on and one design system so that your team can move between needs without switching tools. A few examples include:

Maturity Assessment

Benchmarks your data maturity across seven dimensions in under 15 minutes and identifies the strengths, gaps, and priorities that should guide investment.

Agentic Data Migration

Assigns a specialized AI agent to each stage of a source-to-cloud migration for up to 18x faster migrations while routing low-confidence outputs to human review.

BI Rationalization

Centralizes report metadata across business intelligence (BI) platforms; flags redundant and unused reports; and recommends what to keep, consolidate, or retire.

Cloud Cost Monitoring

Analyzes 30 days of usage on platforms such as Snowflake and Databricks and recommends specific fixes with projected, dollar-quantified savings.

Data Quality Scorecard

Gives your team a clear, measurable view of how trustworthy your data really is.

Operational Dashboard

Shows run history, success rates, and objects processed across every accelerator in one place.

An AI Agent for Every Stage of Migration

Agentic data migration automates source-to-cloud migration from end to end. Each agent scores its confidence in its own output and flags anything uncertain for human review, which keeps your team in control of every change.

1

Source Profiler

Inventories tables, columns, constraints, and row counts.

2

Schema Analyzer

Flags complexity and rates the risk of each object.

3

SQL Converter

Translates data definition language (DDL) to Delta Lake.

4

Schema Builder

Builds the target schema.

5

Data Migrator

Moves the data to the target.

6

Validator

Checks the migrated data against the source.

7

Documentation

Generates a complete record of the migration.

Expand

Schema Analyzer

Each object receives a low, medium, or high risk rating and a confidence score.

Expand

SQL Converter

Low-confidence conversions are flagged with reasons so that your reviewer knows where to look.

Expand

Validator

Row counts, schema conformance, and sample-based checks confirm the target matches the source.

Expand

Documentation

Your team receives the data dictionary, mappings, transformation and validation logs, and DDL without writing them by hand.

Value for Everyone Who Works with Data

MPH for Data serves the leaders who answer for data investments and the practitioners who do the daily work of keeping data reliable.

Data LeaderData Practitioner

ROI and Cost Control

Dollar-quantified savings and one unified view of cloud spend for measurable ROI. Your budget decisions rest on figures you can defend.

Reduced Risk

Trustworthy data and audit trails lower the risk behind every decision. Your leaders can act on insight instead of hesitating over which numbers to trust.

Faster Maturity

Benchmarked progress shows how your data maturity compares with industry peers. You can measure improvement over time and direct investment where it returns the most.

Less Manual Effort

Automation handles the repetitive cleanup and discovery work. Your engineers spend fewer hours on tasks that don’t need their expertise.

One Workspace

Single sign-on gives your team one place to work across every accelerator. No one loses time switching context between disconnected tools.

More Building

Practitioners spend their time delivering insight instead of on janitorial data work. More of what reaches the business is analysis rather than maintenance.

Questions Leaders Ask about MPH for Data

What is MPH for Data?

MPH for Data is a unified platform of AI-powered accelerators that work across the data lifecycle. It helps enterprises assess, migrate, rationalize, and optimize their data environment in one interactive workspace.

Does MPH for Data replace our analytics and BI tools?

No. MPH for Data is tool-agnostic and works with the platforms you already run, including Snowflake and Databricks. It makes your existing environment more trustworthy, relevant, and cost-effective without forcing costly migrations.

How does MPH for Data reduce cloud costs?

Our cloud cost monitoring accelerator analyzes 30 days of usage across platforms such as Snowflake and Databricks. It recommends specific, prioritized fixes with projected dollar savings, which your team can review and apply with a single click.

What happens during an MPH for Data demo?

A Marlabs data expert walks you through the accelerators most relevant to your priorities, using scenarios built on your own stack. As a natural next step, the maturity assessment gives your team a benchmarked baseline.

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Start with a Clear View of Your Data

In a matter of hours, your team can have a measurable baseline and a prioritized roadmap before cloud costs and technical debt climb any higher.

Not ready to talk yet? In the meantime, read our whitepaper on how leading companies use data mesh architecture to build trustworthy, AI-ready data.

Talk to a data expert

Read the Whitepaper

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