The cloud is now really smart, merging with Artificial Intelligence (AI). Now, even a new beauty startup without a data scientist and even a dedicated IT department can figure out a cloud data warehouse to support its booming business model.
Disruption is accelerating the market for data warehousing solutions, leading to a significant augmentation of existing data warehouse strategies. Vendors are providing advanced solutions to data-driven businesses that rely on the effective collection, storage, and integration of data from disparate sources for analysis and insights.
It’s no surprise that the amounts of data generated and analysed, as well as the number and types of data sources, have exploded. By improving greater elasticity, improved scalability and access to on-demand IT resources, the value and demand for cloud has soared during the pandemic, mostly driven by digital acceleration.
Just as more organisations started moving away from traditional data warehouses to the cloud, leveraging the cost savings and scalability that managed services can provide, Oracle, which has been building intelligence into its database, via machine learning (ML) and AI for many years, pipped others with fully autonomous, machine-learning powered, self-securing, self-patching next-generation Autonomous Data Warehouse (ADW).
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Oracle calls the expansion of their ADW “the first self-driving database,” and its goal with the new features is to “completely transform cloud data warehousing from a complex ecosystem into an intuitive, point-and-click experience” that will enable all types of professionals to access, work with, and build business insights with data, from engineers to analysts and data scientists to business users, all without the help of IT.
The ADW makes it easy even for entry-level enterprises, SMBs and companies without much IT expertise — to load data, and cleanse data, run diverse analytical workloads from any source, including departmental systems, enterprise data warehouses and data lakes, as well as automatically create business models, discover patterns to generate insights, achieve faster results, and improve productivity while lowering costs with zero administration.
Despite the doomsayers proclaiming the demise of data warehousing, suggesting that it has become slow and cumbersome to provide insights at the click of a button, the data warehouse is evolving into an integral and essential piece of the big data landscape.
Organisations are investing millions of dollars designing, implementing, and updating enterprise data warehouses, and they are still just about everywhere.
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Data warehouses are playing a leading role in next-generation initiatives, from AI to machine learning to the Internet of Things led by behemoths such as Microsoft, Google and Amazon. Google incorporated machine learning into its BigQuery data warehouse.
Next-generation data warehouses are on-demand, secure, and scalable self-service data centres fully automating the provisioning, administration, tuning, backup, and recovery of data. This accelerates analytics and actionable insights while minimising administration requirements.
With next-generation data warehouses, organisations do not need an innovation-limiting, pre-defined schema that limits their ability to harness insights from available information. With Amazon Web Services, Microsoft Azure, and Google Cloud, immense business benefits are realised that include:
- Creation of a data-driven customer journey
- Enhanced business agility and faster time-to-market, enabling improved and faster decision making
- Reduced infrastructure, maintenance, and admin overhead costs, resulting in improved ROI
- Anytime/anywhere access, enabling self-service BI capabilities
- Automation based on AI/ML
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Research firm IDC expects global spending on public cloud to grow by 21.7 per cent this year to $385 billion and by 2023, over 55 per cent of enterprises worldwide will have replaced outdated operational strategies with cloud-centric models.
As they expand their use of the cloud, most enterprises will employ an enhanced cloud environment that provides easy-to-use, no-code tools that empower data analysts to do tasks that previously required data engineers and data scientists and puts faster, more powerful insights within the reach of organisations of all sizes.
Last year, IT spending on public cloud infrastructure technology, such as servers and data storage, surpassed spending on traditional, on-premise IT for the first time, according to IDC.
As a result, cloud suppliers such as Google, Amazon, Microsoft and Snowflake are battling for leadership in the data warehouses space, which is the epicentre of the data-driven capabilities that every business is looking to build or enhance. But Oracle is taking the market in a new direction, making cloud data warehouses usable by virtually anyone in any size organisation by introducing simplicity.
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It is using automation to deliver a point-and-click, drag and drop experience that’s so intuitive it’s like the iOS of the enterprise cloud data warehouse space.
It’s a big leap forward, and experts say it will continue to innovate without a direct response from its competition, as there are no autonomous, machine-learning powered, self-driving cloud data warehouses available from any other vendor — be it AWS, Snowflake, Microsoft Azure or legacy database vendors such as IBM and SAP.
Oracle is betting that customers will find that its autonomous technology delivers a level of value and flexibility beyond what any competitor can offer. Already, there are thousands of Autonomous Database customers globally, including companies relying on it for data warehousing such as telecommunications leader Vodafone, Siemens Mobility, Accenture, Outfront Media, MineSense, real estate conglomerate Kingold, financial services provider Certegy, and many more.
According to experts, Oracle has come up with the best solution — something no other cloud or database vendor has matched yet. ADW not just lowers the cost for customers because you need fewer people to run it, it also performs better because it’s constantly tuning the system to optimise performance, and it’s one converged data warehouse service. There is no ETL required to move data, no separate services to invoke, as everything is engineered into the same database.
The data warehouse — as a system, as a concept, and as a way to deliver insights about customers, markets, and operations — is increasingly becoming an even more critical part of the digital world. And to get better value from it, businesses are getting smarter, they are voting with dollars for an autonomous cloud data warehouse solution rather than grappling with manual labour-intensive administration and management.
It won’t be a stretch to say then that Oracle ADW might take the lion’s share of the market and leave others fighting.
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