# Databricks consulting in Boston, MA > Biotech and pharma along the Cambridge and Seaport corridors, the research universities feeding them, and one of the largest concentrations of institutional money in the country share a subway line and a rule. If you're on either side of it, a number has to be traceable to what it was read from. Canonical: https://www.techfabric.com/databricks-consulting-boston Serving: Boston, Cambridge, Somerville, Waltham, Providence, Worcester Headquarters: 1530 E Williams Field Rd, Ste 201, Gilbert, AZ 85295. No office in Boston. --- ## Why Boston work is our work When auditors or a validation team ask how a number was reached, a stalled migration and a second lineage tool won't answer them. We move your warehouse onto Databricks with lineage recorded in Unity Catalog and Lakeflow pipelines that can be replayed, so a validation reviews what already runs. Boston's biotech labs and asset managers face the strictest version of that question, and its teaching hospitals ask it too. ## Work a buyer here would recognise Reconciling lab, trial or portfolio data from many systems means seeing exactly where a record failed, which is what the Temporal pipeline built for Athlinks gives. It stitches together more than 400 million athlete records from disparate sources, with granular control, automatic retries and real-time visibility. ## Validation is part of the build Boston's biotechs in Kendall Square and the Seaport keep FDA-bound records under 21 CFR Part 11, which requires secure, computer-generated, time-stamped audit trails, and a changed record can't obscure what was there before. Massachusetts adds 201 CMR 17.00, so a Financial District fund holding a resident's personal information must keep a written information security program. ## Questions ### Can Databricks keep up with the sequencing output of a Boston-area genomics lab? Yes, if the files and the tables are kept apart. The Broad Institute in Cambridge says Broad Clinical Labs has sequenced nearly 900,000 whole human genomes, on average one every three minutes. We'd leave the reads and alignments as files in a Unity Catalog volume and load the variant calls and sample metadata into Delta tables, so a researcher can query variants in SQL without opening a file. Each sample's consent and project go in as columns, and access is granted per project. Sources: [The Broad Institute](https://www.broadinstitute.org/sharing-data-and-tools/cloud-computing) ### Could Databricks handle Massachusetts All-Payer Claims Database extracts for a Boston research team? Yes, and the request process shapes the design. The Center for Health Information and Analysis runs the Massachusetts APCD, which gathers medical, pharmacy, dental and behavioral health claims from public and private payers, with about 60 organizations submitting data every month. An extract arrives through an approved request, so we'd land it in a Unity Catalog schema only that project can read and keep each release as its own versioned table. Every derived table is tagged with the request it belongs to. When the approval ends, downstream lineage from that release lists the derived tables to delete. Sources: [The Center for Health Information and Analysis](https://www.chiamass.gov/ma-apcd/) ### Will Databricks suit Boston data scientists who live in Python notebooks? It should suit them, and Boston has plenty of them. PyData Boston-Cambridge, a Python and machine learning meetup, lists 3,495 members on its Meetup page. Databricks notebooks run the same pandas and PyTorch code, so we'd move the notebooks as they are and change nothing about how people work at first. The difference comes after. A notebook that matters becomes a scheduled job with tests, and the model it trains gets tracked in MLflow with its tables registered in Unity Catalog, so someone else can rerun it next quarter. Sources: [PyData Boston-Cambridge](https://www.meetup.com/pydata-boston-cambridge/events/) ### Do you work under GxP or 21 CFR Part 11? We build to the requirements those impose, which is a replayable pipeline, an immutable record of what changed, and access resolved at read time. Formal validation is your quality team's process and we support it with systems designed to be validated rather than systems that have to be explained afterwards. ## What databricks consulting covers ### Migration off Snowflake, Synapse and Teradata Run through TechFabric Airlift, with executable playbooks for twenty-seven source platforms, signed migration certificates, and a cutover you can reverse at two in the morning. ### Unity Catalog governance Catalogue and schema design, a grant model expressed through groups, row filters and column masks, and lineage that survives a refactor. The boundary your agents and Power BI inherit. ### Lakeflow pipelines Ingestion and Lakeflow jobs with schema evolution handled rather than hoped for, medallion boundaries drawn on purpose, and jobs that recover instead of restarting from zero. ### Databricks Apps and agents Applications that run inside the workspace under their own service principal, and agents on Unity Gateway that inherit catalogue permissions instead of routing around them. ### Genie and AI/BI Metric definitions agreed with the person who owns the number, and a benchmark suite Genie has to keep passing, so the answer holds up when finance checks it. ### Cost that somebody can defend Cluster policies, warehouse sizing, file layout and the queries that actually pay. Instrumented at build time rather than discovered on an invoice. ## Working with us from Arizona Arizona does not observe daylight saving, so we are two hours behind you from November to March and three hours behind from March to November. That leaves most of your afternoon overlapping our morning, which is usually enough. Most delivery is remote or hybrid. We travel for discovery, workshops and the opening weeks of a build.