The difference between a bold decision and a reckless one is insight. Launch’s Data & AI Studio helps businesses cultivate information that empowers a culture of collaboration and creativity, using data operations, data platforms, and data visualization. Save time and money for your organization by partnering with Launch to uncover the strategy, governance, and architecture that helps you achieve your bold goals faster.
Studio Disciplines
Data Architecture Data & Analytics Data Science Data Engineering Power BI Machine Learning
40%
increase in labor productivity results from the efficiencies provided by AI solutions.
$120b
will be spent on AI solutions by 2025, doubling the current expenditure.
Data Without Analytics is Just Numbers
Unstructured data isn’t helpful for anyone. If you want to use your data, you’ve got to harness it. Extracting meaningful information out of numbers takes a multidisciplinary approach backed by the scientific method, statistics, and computer programming. Presto: Now you have the insight and know-how to transform not only your processes, but your entire business.
Are you ready to catch lightning in a bottle? With modern and digitized data capture, data storage, data analytics, and reporting capabilities, you can leap forward on your digital transformation journey.
Data & AI Disciplines: Using Data to Make Tech More Human
Data can transform an organization, from improving operations to enabling better decision-making. From bot building to financial forecasting, natural language processing to predictive analytics, our data scientists and data engineers can make it happen.
The Data and AI Studio focuses on three core disciplines:
Imagine leaving raw meat on the counter for days until you figured out what to make with it. It would spoil, and a potential meal would be wasted. Now imagine your valuable raw data just existing, with no plan for reporting or development. That data might not spoil in the traditional sense, but it is a waste (and often an expensive one).
Turn your data into value with parsing, collating, reporting, and forecasting capabilities.
Descriptive Analytics
End-to-end reporting architecture and design
Data pipeline development
Blueprint design
Data warehousing
Diagnostic Analytics
Historical data
Taxonomy management
Predictive Analytics
Advanced analytical capabilities
Data science implementation
Prescriptive Analytics
Data subscription
Reporting applications
Product/service integration
Data Science
When you think about Artificial Intelligence and Machine Learning, do you think about robots taking over in a post-apocalyptic world? While we are training machines, we can assure you the machines will only take over the designated tasks they were programmed for.
Machine Learning (ML) and Predictive Modeling
Data assessment and preparation
Clean, Augment, Transform, and Integrate (CATI) Data
Exploratory data analysis (EDA)
Model training, testing, and selection
Regression models
Classification models
MLOps, including model deployment
Model performance tracking and improvement
Artificial Intelligence (AI) Solutions:
Historical data
Taxonomy management
Robotic Process Automation (RPA)
Reporting automation
Healthcare claims processing automation
Data collection automation
ML model training and testing
Times Series Forecasting
Trend-season decomposition
Analysis of Variance (ANOVA)
Time series models (ARIMA, Exponential Smoothing)
Monthly forecast automation
Scenario analysis
Data Engineering
If a data pipeline falls and scatters in a forest, and no one is around to hear it, does it make a sound? No. But you’d probably hear some mumbling from nearby data engineers.
While a data pipeline isn’t a physical object, it is still built with purpose by skilled engineers. They collect, analyze and transfer data to be converted into measurable results.
Our data engineering capabilities span from foundation design to deep learning architecture.
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