There’s little debate on the importance of a strong data foundation for AI-powered models. Hence, it’s no surprise that enterprises continue to invest in data warehouses like Teradata, Oracle, and Netezza. Despite their long-standing benefits, these legacy data warehouses have a failure rate of over 50% – primarily due to the following couple of reasons:
- Complex architecture and technical problems
- Inability to meet business needs and requirements
Focusing on the second point, it’s pretty clear that legacy warehouses are both expensive and time-consuming when it comes to delivering real-time data insights to business users. Similarly, the “traditional” Extract-Transform-Load or ETL process is no longer able to perform analytics and provide actionable insights in quick time.
Here’s a representation of how traditional warehouses are currently delivering data-driven insights:
How are enterprises dealing with the challenges of legacy warehouse tools? Let’s explore.
The emergence of Shadow IT
To overcome these hurdles, enterprises are adopting a “decentralized” approach to mobilizing data to address their problems. This has led to the emergence of Shadow IT within “siloed” business teams. Simply put, Shadow IT is the unauthorized use of any IT service which is not approved by the IT team.
In the area of data analytics, Shadow IT offers a decentralized approach for business users to get answers to their queries quickly. While centralization prioritizes security over speed, the decentralized process prioritizes speed over security.
This has led to a host of challenges, including:
- Lack of visibility and control
- Increased chances of a data breach or loss
- High costs and waste
- Inaccurate data analysis – without a “single source of truth”
This is how Shadow IT has added a layer of complexity to the traditional warehouse/ ETL process:
How Onix can help in preparing data for the AI world
As an award-winning Google Cloud partner, Onix can help you with data migration and modernization to the Google Cloud platform. Through our suite of Birds, we can help you automate this process to prepare for various AI use cases such as:
- AI-powered augmented analytics
- AI-powered business intelligence
- AI-first data strategy
Here’s how each of the following Bird products can play a role:
- Eagle
As an end-to-end assessment tool for data migration, Eagle can highlight the limitations of your legacy warehouse and ETL infrastructure. Using knowledge graphs, Eagle can map out the legacy processes and eliminate any AI hallucinations.
Here’s a customer success story of how a U.S.-based insurance company used the Eagle tool to accelerate its data modernization to the cloud. - Raven
As our code conversion and transformation tool, Raven can quickly convert workloads from traditional data warehouses to cloud-native technologies like Google BigQuery. Here are some of the popular data warehouses supported by Raven:- Hadoop
- Teradata
- MS SQL Server
- Netezza
Here’s a customer success story of how a U.S.-based financial services company modernized its data warehouses for powering innovative AI applications.
- Pelican
As our data validation tool, Pelican can validate data and address challenges like inconsistent data, lack of scalability, and time escalation. With its AI-powered automation, Pelican ensures minimum business disruptions after data modernization.
Here’s a customer success story of how a leading banking and financial company used the Pelican tool to improve its data security and customer trust.
Conclusion
With the traditional legacy infrastructure, enterprises are spending too much time on the journey from data collection to delivery of relevant outcomes. To explore new AI possibilities, they need a data-driven solution that can leverage AI technology to accelerate this process.
Onix’s Bird suite accelerates cloud migration by 2x – while lowering migration costs by 50%. As the current CSO of Onix, Dr. Phil Shelley shares his unique perspective on how to transform this modernization process for enterprises to fully benefit from AI technology.
To learn more, checkout our latest asset titled, “Mobilizing Data for an AI-powered world”.
Download the assetReference links:
https://www.timmitchell.net/post/2017/01/10/why-data-warehouse-projects-fail/https://www.crowdstrike.com/cybersecurity-101/cloud-security/shadow-it/
