O: Obtain Data
Either pre-existing, newly gathered, or downloaded from an online data store, Mission Cloud extracts your data from internal or external databases, CRM software, web server logs, social media, or purchased from a third-party vendor.
S: Scrub Data
Data scrubbing, also known as data cleaning, standardizes data to a specified format. Mission Cloud data scientists apply this method in dealing with missing data, correcting data inaccuracies, and deleting any data outliers.
E: Explore Data
Next, exploratory data analysis is necessary for the planning of subsequent data model strategies. Mission Cloud applies descriptive statistics and data visualization tools to help us better understand your data at the outset. We then look for patterns that may require further investigation.
M: Model Data
ML is used to gain deeper insights, forecast results, and predict the best course of action. Our data scientists apply ML techniques like association, classification, and clustering to the training data set, and your model is tested and fine-tuned for functionality and accuracy. Mission Cloud has extensive experience working with Computer Vision, Natural Language Processing, recommendation engines, predictive analytics, and successfully getting ML models to production.
N: Interpret Results
Mission Cloud data scientists and analysts work with you to convert findings into actionable data insights. We use data visualization tools such as Amazon Quicksight to help present trends and predictions into understandable business insights through diagrams, graphs, and charts. Data summarization then helps your business understand and use the results to drive business outcomes.
Data Storage
Amazon Redshift: Perform complex queries against structured and unstructured data for data warehousing.
AWS Glue: A serverless ETL engine for semi-structured data that produces a unified catalog of data in a data lake with metadata to make it searchable.
Machine Learning
Amazon Sagemaker: A fully-managed ML service on Amazon Elastic Computer Cloud (EC2) enables users to scale operations, organize data, as well as build, train, and deploy ML models.
Amazon SageMaker Data Wrangler: Reduces the time to gather and prepare data for ML from weeks to minutes, and you can do everything from a single interface.
Data Analytics
Amazon Athena: An interactive query service that enables rapid analysis of data stored in Amazon S3 or Glacier. It is quick, serverless, and utilizes standard SQL queries.
Amazon Elastic MapReduce (EMR): A service that processes large amounts of data using servers such as Spark and Hadoop.
Amazon Kinesis: Enables real-time gathering and processing of streaming data. It makes use of website clickstreams, application logs, and IoT device telemetry data.
Amazon OpenSearch: Search, analyze, and visualize petabytes of data.
Amazon QuickSight: Business Intelligence (BI) tool for fast and easy data visualization and dashboards without complex integrations.
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