Analytics and Data Summit 2020

The U.S. Census is the nation's largest peacetime mobilization effort. Census data is the basis for the determination of electoral districts and the analysis of population and economic trends by businesses, government, private data analysts, civic associations, and others. In the past, the Bureau relied heavily on paper-based data collection; the 2020 Decennial is transforming to integrate leading edge technology solutions. With the 2020 Decennial Census going mobile and online for the first time, secure technology is a top priority. This session will cover innovations implemented in field operations, online data collection and response data integrity. If technology innovations and best practices in security excite you, then this session is for you! Atri Kalluri, Senior Advocate for Response Security and Data Integrity, will provide a behind the scenes overview on how the 2020 Census is conducted with insights into technical approaches and solutions adopting industry best practices.

School Districts collects vast data points about their students, include gradebook, attendance, formative assessments, summative assessments, final and interim marks, interventions and enrichment, discipline, IEPs, Section 504 plans, diagnostic assessments/universal screening, mastery learning, student feedback and self-assessments, social emotional learning (SEL) observations, progress monitoring, pull-out schedule, and longitudinal data, and deliver through actionable dashboards to the consumers and stakeholders. In this session, you will learn on how LAUSD uses Oracle’s predictive analytics capabilities to identify key factors influencing the predicted lower performance and implement steps proactively to effectively address the factors and improve performance and overall graduation rate across various schools, implement a continuous learning and improvement process.

If you have geospatial data in Oracle Database, you also have a powerful development tool to create map visualizations with that data. In this session, we will provide an overview of the various visualization strategies and platforms our customers can use to visualize and explore their Oracle Spatial managed data sets.Learn how to effectively utilize the Spatial and Graph Map Visualization Component (formerly known as MapViewer) to query and serve your Oracle Spatial data in a variety of industry standard formats such as GeoJSON, Image Tiles, and Vector Tiles, as well as OGC standards-based services such as WMS. Examples and demos will show how to use various Open Source HTML5, WebGL mapping clients, and APIs to consume and visualize data services provided in the Map Visualization Component. We will also show how to use the HTML5 Map API provided by the Spatial and Graph Map Visualization component to digitize and modify your geometry data stored in Oracle Database.

Want to learn how to easily create interactive maps and perform spatial analysis on your data? In this session, we’ll show you how Spatial Studio lets you quickly and easily do spatial analytics and create maps, even if you don’t have GIS or Spatial knowledge. Business users and non-GIS developers have a simple user interface to access the spatial features in Oracle Database. Spatial Studio simplifies the development of web applications, SQL analysis, and REST services using the full spectrum of spatial operators and functions in Oracle Spatial and Graph. We will show you how you can prepare your data for spatial analysis, perform spatial analysis operations, publish, and share the results. You will also learn how you can access spatial analyses results via REST and incorporate in applications and workflows.

From land management and transportation, to mapping and location analytics for business, many applications have demanding spatial processing requirements that are addressed by powerful functionality in Oracle Spatial and Graph. Learn more about use cases that leverage advanced spatial features of Oracle Database, now included in almost every database edition, in the cloud and on premises. This session will cover features such as parallel enabled spatial operators and functions, parallel enabled server side clustering (cluster millions of geometries in seconds), local partitioned spatial data and indexes to maximize manageability and performance of massive spatial datasets and workflows, and processing techniques to determine paths covered by positions collected with GPS-enabled devices. Customer use cases and code examples will be included. This session is intended for a technical audience, but others will also gain useful insights on Oracle’s powerful spatial capabilities.

Two case studies at large South African government entities with high volumes of data.Oracle Spatial and Oracle Workspace Manager have been used extensively, over many years, in two South African Government agencies, namely: NGI: National Geo-Spatial Information - A component of Department of Rural Development and Land Reform, and SANRAL: South Africa National Roads Agency SOC Limited. The session will describe the complex heterogeneous environments and large datasets managed by these two entities and demonstrate how Oracle data (both spatial and non-spatial) form an integral part of managing the business of these two agencies. Oracle Workspace Manager has been implemented to add the 4th dimension to GIS, namely time. Spatial data validation and Cleanup and Processes that were implemented to address data quality and validity will be discussed.

Data mining is the key driving process in any business world. Data is available in many forms and one such data set is spatio-temporal (ST) data, which has both spatial (Geographic) and temporal (Time) component. Spatial data is analyze on various levels like, zip codes, census tract, state, geocode, etc. Temporal data captures various data points per observation over time line. Both these dimensional data provides significant correlation and make the analysis more effective. However, we should keep an eye on the existence of autocorrelation in ST, before blending with another data set to remove bias. In this use case, we can see how using Oracle Autonomous Data Warehouse (ADW) as data source and blending the spatio-temporal data in Oracle Analytics Cloud (OAC, for visualization) gives an immense opportunity for businesses to adopt change management effectively.

Oracle Spatial Studio is a self-service web application that makes it easy for business users, analysts, and developers to create interactive maps and perform spatial analysis on their business data, from Oracle Database or other data sources. It provides a simple user interface to access the spatial features in Oracle Database. In this hands on lab session, we will walk through using Spatial Studio to prepare your data for spatial analysis, perform spatial analysis operations, publish, and share the results. You will learn how to access spatial analyses results via REST and incorporate in applications and workflows. Also, we’ll cover advanced topics for developers, such as managing complex 3D and GeoRaster data sets; visualizing 3D scenes, clusters and heat maps; and exploring data sets with huge data volumes in a high performant and highly interactive manner.

In this session for developers, we will cover various advanced topics on using Oracle Spatial Studio effectively for applications with demanding geospatial processing requirements. Topics include managing complex 3D and GeoRaster data sets; visualizing 3D scenes, clusters and heat maps; and exploring data sets with huge data volumes in a high performant and highly interactive manner.In depth explanations will be provided on how Spatial Studio manages an unlimited number of ad hoc analyses, and how to enable data sampling and pre-caching vector tiles for your most frequently used datasets to achieve better performance. Examples will also be given on how to fully automate (using scripts) your typical geospatial data management and analysis workflows using the programmatic RESTful end points of Oracle Spatial Studio. We will also provide a sneak peek of the exciting new features coming in the next versions of Oracle Spatial Studio.

Python is hugely popular for data analysis, including geospatial data. The ecosystem of specialized geospatial Python libraries continues to grow and evolve, providing a powerful toolkit for developers to supplement the spatial features of Oracle Spatial and Graph. Spatial-temporal analyses uses specialized algorithms to answer questions such as 'Is the change over time in traffic accidents for an area related to the change over time in nearby areas?', and 'Are historical traffic accidents clustered in both location and time?'. Spatial-temporal analyses then uses these results to predict the likelihood of potential future outcomes. This session will cover the basics of using Python with Oracle Spatial and then demonstrate a spatial-temporal use case based on a historical dataset of nationwide traffic accidents.