Data science efforts generally encompass several common underlying services, which we’ve listed below. We customize and combine these services to meet your organization’s specific needs. Please contact us if there are additional unlisted services that you need assistance with.

Data Cleaning

The 80/20 rule is frequently cited in data science. This rule simply states that collecting, cleaning, and organizing data typically accounts for 80% of a data analysis effort, leaving only 20% for mining data for patterns, building models, and generating reports. We have extensive experience cleaning data, and we automate as much of this process as possible to minimize cost. We can also provide guidance for your data collection and storage methods, in order to minimize any future data cleaning requirements.

Cloud Services and Cloud Migration

Migrating your data from local legacy systems into the cloud permits your data to be analyzed with the latest Artificial Intelligence tools. It also allows your data to be securely accessed by your team with no regard to location. Cloud storage is often the safest solution for storing data. Backups can be automated to prevent data loss or corruption. For example, Amazon’s S3 guarantees 11-9’s durability (99.999999999%), which means

“if you store 10,000,000 objects with Amazon S3, you can on average expect to incur a loss of a single object once every 10,000 years” –Amazon

We keep current with the latest services for migrating and managing files and databases in the cloud so that we can explore the options that best fit your needs.

Pattern Recognition for Business Insights

Recognizing patterns in data and capitalizing on those insights is paramount to data science. We provide data analysis services using conventional statistical approaches, such as ANOVA and Regression Models, as well as analyses using advanced Artificial Intelligence algorithms. We currently have an affinity for the AI platforms offered by Amazon and Google, and we also have experience with Python libraries such as Pandas, Scikit-learn, TensorFlow and Keras. The AI landscape is rapidly evolving and we enjoy keeping current with the latest tools for efficiently developing business insights.

Data Visualization and Application Development

We are able to provide static, one-off reports, as well as periodic or real-time reporting and interactive data visualizations. We have seven years of experience developing modern web applications, including several apps for research and data visualization. We have built several custom administrator dashboards and we’re experienced with graphing libraries such as Ploty and D3. We suggest and prefer developing responsive web applications in order to eliminate installations and updates.

Application Programming Interfaces (APIs)

APIs are the underlying communication mechanism between databases and applications. Many modern web services such as Google Maps, UPS, and Facebook publish APIs that allow developers to interact with and incorporate their services into custom applications. We have extensive experience in both consuming APIs, and developing our own APIs. We’ve developed RESTful APIs for many years, and we’re huge fans of GraphQL, a new query language developed by Facebook. GraphQL is a modern method of describing data structures, and it allows us to combine many data sources, regardless of format or structure. With GraphQL, APIs that we develop can evolve over time to adapt to your changing business needs with minimal programming effort. Additionally, GraphQL minimizes data transfer, which results in faster applications and reduced costs.