Data warehousing is a rapidly growing and exciting area of technology because warehouse applications provide insightful information. In turn, these insights result in an operational or marketplace advantage for the organization.
While keeping the OLTP systems in top condition is a full time focus for many, warehousing has become a must-have skill. Through this technical webcast, you can quickly expand your level of understanding on data warehousing technologies.
Join Jessica Rockwood, IBM warehouse development and performance expert, to learn the current technologies in warehousing and what is needed in the future. Jessica will review core principles - the why, what, and how of warehousing. Then, she’ll cover current day challenges and the new capabilities needed for warehouses of the future.
Attend this talk to expand your warehousing knowledge.
Hear Snowflake’s founders explain why the data warehouse needed to be reinvented and the new architecture they developed for it.Read more >
Jana's mission is to bring internet access to over a billion people in emerging markets via mobile applications. Already driving more than 3.8 billion MB of app usage, Jana needed a scalable and cost-effective solution to process and analyze that data.
Snowflake and AWS are helping Jana keep up with the demands of processing and analyzing that rapidly growing stream of data. Using Amazon S3 and the Snowflake Elastic Data Warehouse, Jana processes and analyzes app usage data in a high-performance, scalable way without the cost and complexity of other solutions.
Join us to learn:
- How Jana made the transition from MySQL to a cloud data warehouse
- The data pipeline that Jana designed to move data from source to analysts
- The benefits Jana realized as a result of moving to a cloud infrastructure and data warehouse
Who should attend?
Data scientists, analysts, and anyone who needs to understand how to make critical data rapidly available - without capital expenditures.
Learn how cutting-edge cloud technology from Informatica and Snowflake allows you to bring together and analyze data in minutes to hours rather than days.
Listen in as we discuss:
--Taking advantage of the elasticity and scalability of Snowflake via native integration of Informatica + Snowflake
--Joining diverse on-premise and cloud data sources
--Simplifying the data pipeline to get data from source to analysts faster without sacrificing data quality
+ Use cases with a live demo, and interactive Q&A
In this webcast, Jason Pohl, Solution Engineer from Databricks, will cover how to build a Just-in-Time Data Warehouse on Databricks with a focus on performing Change Data Capture from a relational database and joining that data to a variety of data sources. Not only does Apache Spark and Databricks allow you to do this easier with less code, the routine will automatically ingest changes to the source schema.
Highlights of this webinar include:
1. Starting with a Databricks notebook, Jason will build a classic Change Data Capture (CDC) ETL routine to extract data from an RDBMS.
2. A deep-dive into selecting a delta of changes from tables in an RDBMS, writing it to Parquet, querying it using Spark SQL.
3. Demonstrate how to apply a schema at time of read rather than before write
In recent years, some users have harbored concerns about clouds in general, as well as their use in data warehousing. As the number of user organizations practicing elastic data warehousing on clouds has increased, the track record of success has helped other users get past perceptual barriers and other myths concerning security, multi-tenancy, and interfacing with clouds.
We all know that data warehouses and users’ best practices for them are changing dramatically today. As users build new data warehouses and modernize established ones, they are turning to cloud-based elastic data warehousing, because the automation of elasticity yields agility, ease of use, scalability, and performance, while reducing maintenance, tuning, capital investments, and other costs.
This webinar will:
- Demystify elastic data warehousing by debunking myths about it
- Define elastic data warehousing and its goals in terms that data management professionals and business users can relate to
- Show how cloud-based data-driven tools and platforms have proved themselves, such that users are now more comfortable adopting them
- Discuss the real-world benefits of data warehousing, data management, and analytics on elastic clouds
- Explain how data warehousing solutions built to leverage the full capabilities of an elastic cloud can satisfy new requirements for analytics, big data, data streams, and multi-structured data
Data visualization tools empower Business Analysts to synthesize millions of variables and piles of spreadsheets into functional dashboards. Unfortunately, in many companies, the need for better data is not part of the drive for better dashboards.
The reality is, today’s data visualization tools are only as good as the data they reflect. Helping users consolidate, transform and deliver the most accurate and up-to-date information is critical to leveraging your dashboards and the data behind them. In this live webinar, you’ll learn:
• actionable steps to improving data prep for data visualization
• why agile data governance and management is key to data visualization success
• strategies for adopting an agile, self-service approach to data access, analytics and visualization.
Lyndsay Wise joined EMA in 2015 as Research Director for Business Intelligence (BI) and Data Warehousing, focusing on data integration, data governance, cloud technologies, data visualization, analytics, and collaboration. In 2007, Lyndsay founded WiseAnalytics, a boutique analyst and consulting firm focused on business intelligence for small and mid-sized organizations. She has over 10 years experience in software research, BI consulting, and strategy development, specializing in software evaluation and best-fit solution selection. Lyndsay is also the author of Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize ROI.
Chris Bradley continues to explain the different disciplines in the DAMA DMBoK 'wheel' - this time concentrating on Data Warehousing and Business IntelligenceRead more >
Most enterprises are still deciding what the core components of a cloud data warehousing and analytics solution should be. Come see how Red Hat deployed a secure cloud data warehousing architecture inside Amazon VPC using Amazon Redshift and S3. In this in-depth session, get practical advice on how Red Hat shortened the timeline to ingest new data sources and optimized query performance. Also learn how creating virtual data marts can lead to greater agility and faster insights.Read more >