GoogleNextOnAir invites us to connect digitally, collaborate, and solve together the most important challenges that businesses face today. Wizeline is a Google Cloud Partner and we would like to share with our customers and community what we learned during week 5 of this fully-digital event.
Register today and join upcoming sessions on Application Modernization, Cloud AI, and more.
- BigQuery and multi-cloud are the centerpieces of the Data Analytics weeks at Google NextOnAir. Google launched BigQuery Omni, built on Anthos, to be able to process multi-cloud data, bringing the Dremel compute engine capabilities to the data.
- Google makes it very easy to modernize your data warehouse and data lake with superior data catalog and data governance capabilities that help to plan and monitor resource allocation and utilization.
Data is Growing Exponentially
Some trends that are driving changes:
- A 5x growth in enterprise data.
- By 2025, more than 25% of data will be real-time in nature.
- Less than 1% of unstructured data is analyzed or used (and ~80% of all data is unstructured).
- Unprecedented market shifts post COVID.
Google encourages organizations to:
- Collect, process, store, analyze, and activate their data.
- Aggregate data from first-party and third-party sources, as well as unstructured or new data sources.
- Use solutions-blueprints to simplify the customer journey.
Innovate with Data
Google suggests that data modernization should include the following steps:
- Move your data to Cloud: Traditional enterprise data warehouse implementations often hinder business transformation. By migrating to the cloud you can cut the total cost of ownership (TCO) massively, in many cases above 60%, and simplify operations.
- Open up access and data culture: Data platforms and roles are converging and need to interoperate more often and better. Break down data silos securely and with governance control while allowing for simpler cross-team collaboration.
- Leverage AI: Google Cloud is ready to help your organization make decisions in context, faster, and with real-time artificial intelligence. BigQuery ML provides the capability to create and use machine learning models easier than ever before.
- Leapfrog with automated AI Solutions: Google Cloud has end-to-end packaged artificial intelligence solutions that are easy to use, fast and reliable. You can leverage AutoML Video to build engaging video experiences or use Google’s new Contact Center AI to provide better customer support with the AI Conversational Core.
- Empower teams at scale: Google Cloud provides the options for organizations to decide which solution best fits each data use case. Either using AI out-of-the-box, combining building-blocks, or creating a custom AI on your own terms.
Open and Multi-Cloud Data Platform
Organizations, small and large, don’t need to worry about infrastructure, monitoring, servers. Let’s learn more about Google Cloud’s open, intelligent, and flexible data platform:
- Open: 80% of users work with more than one multi-cloud provider. Looker, a Business Intelligence data platform can be used with any cloud and/or on-premise. BigQuery Omni, powered by Anthos, allows having a single interface in a multi-cloud environment, eliminating data silos.
- Intelligent: Fully integrated artificial intelligence system with solutions to solve real business problems. We have a solution that allows organizations to democratize insights of everyone in the company.
- Flexible: Solutions for different business models with flexible pricing models according to different use cases. For example, to access data, a Data Scientist uses API, a Data Analyst uses SQL interface, a Business Analyst uses a BI tool, a non-technical person can use Data QnA with natural language requests.
Data Warehouse Modernization
Google brings its 10+ years of proven and improved technology, BigQuery, to organizations in retail, healthcare, financial services, media, telecommunication, manufacturing. The total cost of ownership is lower than other cloud providers in the market. Performance has improved from a couple of terabytes to 100s petabytes without having any query performance degradation. BigQuery offers a multitude of options to set up batch and real-time analytics, closing the gap between Data Engineers and Data Scientists through integrated AutoML, matrix factorization, anomaly detection, time series, and TensorFlow modeling options using simple SQL. You can now move a Machine Learning model to production much faster and responsive by leveraging the computing power of BigQuery.
Data Lake Modernization
Google’s Data Lake options are built on open source fundamentals, using fully managed services and facilitating the transition towards a connected architecture that is not locked to a particular service. The total cost of ownership is lower than other cloud providers in the market, and even lower compared to on-premise solutions. Google Storage, Dataproc, BigQuery, Dataflow, Looker, and other products can be combined seamlessly. Twitter, for example, has one of the largest managed Data Lakes, with more than 500k computing cores, 300PB of storage processing more than 1 Trillion messages per day.
Data Governance and Data Catalog
Data Catalog offer is based on Data Catalog Genesis, technology created and used by Google. With traditional solutions, users need to do the heavy lifting, manual tagging, and organization. With Smart Data Catalog you will, access automated metadata creation from BigQuery/Pub Sub/Cloud Storage, use auto-tagging of Personally Identifiable Information (PII) data fully integrated with Data Loss Prevention (DLP), create metadata tags from any source e.g. Oracle, RedShift. Data Catalog leverages a built-in search technology from Gmail and Google Drive. The generated metadata can be paired with Data Governance defined rules to manage access control to the data.