Unstructured data is any data that cannot be readily organized into a relational database or spreadsheet, and cannot be easily analyzed or searched. It makes up more than 80% of enterprise data* and is growing 55% - 65% annually.
Given this footprint and growth, unstructured data presents a large opportunity to gain insights into your business, customers and value chain that can enable greater business success. You need the right data management and unstructured data analytics technologies, skills and IT processes to help you organize, parse, search and analyze your unstructured data.
Rackspace Technology™ brings unbiased multicloud data management expertise to accelerate the value of your unstructured data and cloud. By putting your unstructured data into the right data lake and deploying the right analytical tools, we help you use new insights to create new revenue streams, drive superior customer experiences, and improve business execution and agility — all while protecting your data.
*Sourced from Datamation "Structured vs Unstructured Data"
Organize your unstructured data for maximum benefit.
- Collect data from separate sources and make it easily searchable, and enhance discovery, unstructured data analytics and reporting capabilities for the business.
- Incorporate data from a wide range of non-relational sources including social media, video, graphics, text files, text messages, satellite imagery, surveillance data, data generated from sensors and other IoT devices, log data and scientific data.
- Generate actionable business insights using artificial intelligence processing, analytics tools, business rules engines and intelligent event processing.
Gain new levels of insight into your customers’ views of your company, products and services.
- Understand the results of marketing campaigns, real time sentiment about your company, employees, products, or services, and identify online opportunities and threats.
- Get detailed contextual and tonal analysis beyond simple search, which only provides basic information such as how often posters mentioned the company name after an announcement.
- Understand the customer experiences you deliver from the customer point of view.
Take preemptive and proactive measures against non-compliance and fraud.
- Use your unstructured data with AI and machine learning tools to discover fraud and non-compliance related to cell phones, insurance claims, tax return claims, credit card transactions, government procurement and more.
- Effectively test, detect, validate, correct errors and monitor control systems for fraud and activities that lead to non-compliance.
- Apply unstructured and structured data analytics techniques such as data lakes, data mining, data matching, regression analysis, clustering analysis and gap analysis.
"In our data lake, we now have around 10.2TB of data powering five to six machine learning use cases on the cloud. This generates over 450,000 predictions per day — each of which is generated in just 1.1125 milliseconds. These machine learning models will help automate more processes to drive greater efficiencies that help us optimize performance and cost."See the case study
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