Data Science Projects That Shape Your Business Strategies
We take the time to understand your pain points and exactly how you want to extract and view your data. There are key insights hidden within your swaths data, and we’ll help you discover them.
Our data scientists capture the requested data, maintain it via data warehousing, process and analyze the information, and communicate specified datasets with striking visualizations at the completion of data science projects.
Our team can build complex quantitative algorithms to organize and distill large amounts of information that answer our clients’ questions and assist them in creating organizational strategies.
We’ll pull data from various sources and centralize it into data warehouses, such as Snowflake and Azure SQL. Our team creates the infrastructure to extract, transform, and load the data into a centralized repository. From there, we analyze the data and present it visually so you can take action.
By leveraging dashboards in Power BI and Tableau, our data scientists will highlight trends, key performance indicators (KPIs), and other various metrics required to make truly informed business decisions. Past projects have included student/school/district average daily attendance or the percent of COVID vaccines used throughout California.
Our data storytellers apply machine learning techniques for our clients’ data science service projects to create adaptive algorithms identifying the statistical significance of metric characteristics.
Make sense of the data your organization collects by contacting CTS and our data science experts today.
The Process behind CTS Data Science Projects
1. Research and Define
What story are you trying to tell with your data? What questions can a deep dive into your organization’s data answer for you? Our team at Capitol Tech Solutions aren’t just data scientists – we’re data storytellers. We’ll identify your pain points and help you define how to view your data.
After we understand your goals, we gather the raw structured and unstructured data from relevant sources, including manual entry, web scraping, and real-time data capture from systems and applications.
3. Prepare & Maintain
Our data scientists convert the raw data into a consistent format for analytics, machine learning, or deep-learning models, including cleansing, deduplicating, and reformatting datasets.
At this stage, our data storytellers examine the biases, patterns, ranges, and distributions of values within the data to determine if it is suitable for predictive analytics, machine learning, and complex quantitative algorithms.
At this stage, we transform your data into actionable insights for your organization by deploying predictive analytics, machine learning, or complex quantitative algorithms to find and extrapolate trends in the datasets.
Then we showcase the stories hidden within your data by presenting visualizations, like dashboards, reports, and charts. We highlight key performance indicators with tools like Power BI and Tableau.
Technologies we use in data science projects for clients
- Power BI
- Azure SQL
- Oracle SQL
- MSSQL (Microsoft Partners)
- Azure Cloud Database (Microsoft Partners)
- Microsoft Access
- Azure Tables (Microsoft Partners)
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