Part 2 of 3-Post Series: Architecting Advanced Data Platforms to Support Data Management
‘Smart’ or cognitive solutions are all the rage in today’s data-driven world. Specifically, solutions like AI, machine learning and data analytics that help your business ‘think’ and leverage data more effectively. The future of these cognitive solutions is expected to flourish in the coming years due to billions of investments pouring into the cognitive solutions vertical.
But what’s driving this market for cognitive data solutions? First, data is really, really important and valuable. Secondly, there is a general desire to make business processes more intuitively intelligent to drive competitive advantage in the modern business environment. This smartening, if you will, of the business is absolutely necessary to allow leaders to respond to market trends, positively impact customer experience, and to adapt to a quickly evolving digital economy. Without these smarter solutions, businesses are anchored and are left responding reactively to market dynamics.
The bottom line: This increase in demand for data-driven solutions is a direct outcome of the digitization and generation of a massive amount of data across industries. And that data footprint will only continue to grow. In the first post of this three-part article series, I noted that the amount of data generated in the world will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025. To put that into perspective, 90 percent of the world’s data was generated in the past two years. And when it comes to managing all of this data, the market is responding: Analysts forecast that the global cognitive solution market will grow at a CAGR of almost 50% during the period 2018-2022.
Compelling stats but you’re probably asking why should I care? Fair and here’s why you should: It’s these cognitive solutions that draw insights from business process data and make data-based predictions to augment human decision-making capabilities. That alone is a pretty big deal, but imagine what you can do if you had to do nothing – ie, if you could automate and data ingestion and processing? If you ask me, that’s when the exciting part (the piece that gets the executive office engaged) takes place.
It’s exciting because the business can leverage smarter solutions to make better decisions with a level of visibility at the forefront of digital transformation, allowing organizations to truly capture the momentum of the market. Imagine being able to tell which products are doing better in specific markets based on patterns that your data warehouse helps you find proactively. Or, being able to dynamically customize retail and shopping experiences based on data and previous client interactions. From a competitive perspective, solutions like sentiment analysis allow you to leverage machine learning to better understand market sentiment around your services, as well as those of competitors.
There are security examples when it comes to cognitive solutions as well. AI-driven security features can detect anomalous behavior and take action proactively. Similarly, cognitive systems can also help detect and stop fraud based on data metrics. When it comes to cognitive engines, smart quickly becomes the new normal.
Oracle Autonomous Data Warehouse does exactly this. It uses applied machine learning to self-tune and automatically optimize performance while the database is running. You’re literally working with a solution that gives you foresight into the market to help disrupt and transform the kinds of service and products you deliver. Built on next-generation autonomous technology, Oracle Autonomous Data Warehouse uses artificial intelligence to deliver unprecedented reliability, performance, and highly elastic data management to enable data warehouse deployment in seconds. Oracle Autonomous Data Warehouse brings new meaning to the concept of automatic or ‘autonomous’ data management. Here’s what that means:
- Self-Driving. If Oracle Autonomous Data Warehouse had wheels, it would drive itself. However, the self-driving element here refers to a fully managed data warehouse cloud service that takes care of network configuration, storage, and database patching and upgrades for you. No customer DBA required.
- Self-Securing. This part is truly revolutionary and a first of its kind in our industry. The self-securing part of the database ensures that the architecture always runs the latest security patches. It will also detect anomalous behavior and conduct updates, all on its own, autonomously while still running! Further, the data at rest is encrypted by default using Transparent Data Encryption (TDE). Finally, database clients use SSL/TLS 1.2 encrypted and mutually authenticated connections. (We’ll get much more into the unique self-securing architecture in the third blog of our series.)
- Self-Repairing. No one wants to experience an outage. It causes a lot of stress and can impact, even halt, the flow of your business. Oracle Autonomous Data Warehouse has automated protection from downtime, purpose-built into the core of the design. High availability is built into every component, and backups are completely automated. This means you can get your nights and weekends back knowing you’ve got a data platform that’s actively working to keep your stuff operating.
Sounds cool, right? Let’s pop the hood of this autonomous data vehicle and see how it really works.
Here’s what the Oracle Autonomous Data Warehouse looks like:
Oracle Autonomous Data Warehouse is your direct engine and integration point into the entire DevOps process. Most of all, data-driven applications can leverage machine learning to deliver powerful results while utilizing local services alongside third-party solutions. This means that your existing developer tools, data integration services, data visualization, and cloud object storage easily integrate with Oracle Autonomous Data Warehouse while still leveraging the power of cloud.
To get the most value out of the data, you can visualize it in any way you require. Leverage the Oracle Data Visualization Desktop or use your own third-party business intelligence or data visualization solution.
Oracle Data Visualization
Finally, and this is more of the revolutionary part, Oracle machine learning provides a notebook application designed for SQL users and provides interactive data analysis that lets you develop, document, share, and automate reports based on sophisticated analytics and data models.
Oracle Machine Learning Notebook
Oracle Machine Learning SQL notebooks, which are based on Apache Zeppelin technology, enable teams to collaborate, build, evaluate, and deploy predictive models and analytical methodologies.
From there, this SQL notebook acts as an interface for data scientists to perform machine learning in the Oracle Autonomous Data Warehouse (ADW). These notebook technologies support the creation of scripts while supporting the documentation of assumptions, approaches and rationale to increase data science team productivity.
With greater levels of built-in automation and intelligence, you can couple the data warehouse with powerful machine learning and cognitive solutions. This allows for fast and easy collaboration between data scientists, developers, and business users as it leverages the scalability and performance of the Oracle platform and its cloud services.
Let’s recap. In a nutshell, here are some of the benefits of a data-driven, autonomous solution, specifically, Oracle Autonomous Data Warehouse:
- Simplified, end-to-end management of data and data warehouse resources
- Fully tuned and ‘ready to go’ for your data requirements – including high performance, out of the box
- Fully elastic scaling with intelligence around idle-compute shut off
- Auto-scaling based on dependencies and real-time workload requirements
- Ability to support solutions running on premise, hybrid, or multi-cloud
- Ability to leverage native or third-party data integration tools
- High-performance queries and concurrent workloads: Optimized query performance with preconfigured resource profiles for different types of users
- Powerful data migration utilities to move vast amounts of data
- Deep integration with data storage, repository, and processing engines including Amazon AWS Redshift, SQL Server, and other databases
If you’re worried about security (and who isn’t), we’ll cover that critical topic in part three of our series where I’ll dig deeper into how Autonomous Data Warehouse stores all data (in rest and motion) in encrypted format.
Final Thoughts: The Future is Data-Driven. Make Sure You and Your Data are Ready
It doesn’t matter what vertical you’re in or how big your company is, data impacts your future. Those organizations that find ways to not only leverage data, but also make it easy to do so, will find meaningful, competitive advantages in a digital economy.
From my point of view, Oracle’s Autonomous Data Warehouse provides an easy-to-use, fully autonomous database that scales elastically, delivers fast query performance and requires no database administration. This is the kind of technology that removes the complexity around working with data. Most of all, it allows you to truly leverage the power of data to do innovative and bottom-line enabling activities in a data-driven future.