Our Services

We care for your data at all stages of its lifecycle.

Discover the many ways we can support your business.

Your data needs to reside somewhere. We’ll help you find and build the right place for it. Examples include:

  • Creating tables and views in relational (SQL) databases
  • Building document collections in NoSQL databases
  • Designing appropriate buckets for object storage
  • Designing for transactional (mainly write-focused) use or analytic (mainly read-focused) use
  • Loading setup data required for initial use
  • Writing stored procedures and packages

Platforms we commonly use (if you don’t see yours here, we can probably still work with it):

  • Relational databases: Access, Db2, MariaDB/MySQL, Oracle, Postgres, SQLite, SQL Server, Teradata
  • NoSQL databases: CouchDB, Elasticsearch, MongoDB, Neo4j, Redis
  • Cloud databases: AWS (Aurora, DynamoDB. Neptune, Redshift), Azure (Cosmos DB), GCP (BiqQuery, Bigtable, Spanner), Snowflake
  • Object storage: AWS S3, Azure Blob, Google Storage

Once it is stored, your data still needs to be actively managed for operational use. We can help you with:

  • Comprehensive security planning and implementation
  • Backup and recovery (analysis, execution, and continuous verification)
  • Capacity planning and management, including scale-up of an existing database to take more traffic
  • Performance tuning
  • Proactive monitoring
  • Incident response

Platforms we commonly use are essentially the same as the list above, but if you don’t see yours here, we can probably still work with it.


As your needs change, sometimes you’ll decide you want to switch the kind of database you’ve been using or where the database is running. You’ll need to move the data you have to the new database and because of potential differences (overt and subtle) between the two locations, the process of migration can be challenging. We can help you migrate:

  • From one kind of relational database to another (say, from a licensed product to an open source alternative)
  • From a relational database to a NoSQL database (or vice versa)
  • From an on-prem database into the cloud (or vice versa)
  • From one server to another

Platforms we commonly use are essentially the same as the list above, but if you don’t see yours here, we can probably still work with it.


Data is essential to your operations and you’re collecting a great deal of data in the course of running your business. However, beyond the immediate operational importance of an order, phone call, or website visit, there is valuable understanding to be gained. We’ll help you get the most out of your data by:

  • Building reports that answer complex questions, highlight patterns, and reveal trends
  • Creating visualizations that show the most salient details at a glance
  • Designing engaging presentations that tell persuasive, compelling stories

Platforms we commonly use (but if you don’t see yours here, we can probably still work with it):

  • Any kind of relational (SQL-based) database and most NoSQL databases
  • Plain text files, whether they have a regular structure or not
  • Access, BIRT, Crystal Reports, Excel, Jasper, Power BI, Looker, Metabase, Mode, Pentaho, QuickSight, SSRS, Tableau
  • Keynote, Google Slides, PowerPoint, Visme

Queries and reports are great when you know the questions you need to ask about the data. However, sometimes you want to understand a dynamic or make predictions about the future and you don’t know what questions you need to ask. Machine learning methods were born to help us predict and understand in such situations. We can help you:

  • Build models that help explain why certain things are happening
  • Make predictions about future outcomes (based on past data)
  • See hidden patterns and associations that are difficult for humans to detect

Platforms we commonly use (but if you don’t see yours here, we can probably still work with it):

  • Python, PyTorch, R, Scikit-learn, TensorFlow
  • Azure ML, Databricks, Google Cloud ML, Minitab, Sagemaker, Scikit-learn, SPSS

Basic statistics, such as sums, counts, and averages, are commonly useful. However, other situations require deeper statistical analysis techniques that enable judgments about the world to be made with quantified certainty. We can help you:

  • Sample data effectively (the right amount, the right kind, the right way)
  • Determine the likelihood of some outcome
  • Define the range in which a value is likely to fall
  • Decide if there is a relationship between two sets of variables

Platforms we commonly use (but if you don’t see yours here, we can probably still work with it):

  • Python, R, Scikit-learn
  • Excel, Minitab, SPSS

Different databases have different purposes, so you’ll often need to copy data from one place into another and possibly to modify it along the way. For example, you might need to combine data from a sales database and an HR database into a third database to see if training attendance is having any impact on sales. Whatever your motivation to duplicate your data, we can help you:

  • Pull data from source systems, prepare it to be merged with other data, and copy it into a data warehouse or data mart
  • Copy raw source data into a data lake so that it can be prepared and used later
  • Create repeatable, automated pipelines for recurring ETL and ELT (which does transformations after the load)
  • Evaluate and use “query fabric” solutions that allow you to query multiple data sources at once without first combining them in a centralized place

Platforms we commonly use (but if you don’t see yours here, we can probably still work with it):

  • Airflow, AWS Glue, Azure Data Factory, dbt, Google Cloud Dataflow, PDI (Pentaho Data Integration), SSIS (SQL Server Integration Services), Talend
  • AWS Athena, Starburst, Trino

When you want systems to interact automatically with your data, it is common to expose an API (Application Programming Interface) that the consuming system can use to query and edit (as needed) your data directly. We can help you to:

  • Expose data for secure, automatic consumption
  • Enable automatic data creation and updates
  • Monetize your data as part of a SaaS (software-as-a-service) solution

Platforms and technologies we commonly use (but if you don’t see yours here, we can probably still work with it):

  • FastAPI, Flask
  • GraphQL

Sometimes the data you need will be embedded in formats meant for human consumption, such as web pages and PDF documents, rather than in formats that machines can use easily. When that’s the case, we can help you:

  • Extract data from web pages and other human-centered documents
  • Store the results in a database or similar form
  • Mimic human login and navigation (when needed)

Technologies we commonly use:

  • Beautiful Soup, Selenium, Scrapy