Mobilizing Data for an AI World page 2
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“I need to solve problems and do it on my own terms and timeline.”
With the growing reliance on data, “traditional” data engineering practices, which include ETL and data warehouses,
struggle to deliver on business needs. This led to the emergence of shadow IT – which empowers individual business
teams (or citizen developers) to choose their analytics tools and processes to solve their business problems.
This “decentralized”approach primarily prioritizes speed over security. Here’s how it compares to a “centralized” approach:
Modernization of legacy ETL, data warehouses, and BI, and moving to an AI-driven analytics landscape will provide enterprises with a host of benefits, including:
Here are some benefits of data pipeline and data warehouse modernization:
Through the modernization process, enterprises can significantly improve their analytics capabilities in terms of scalability, security, and governance, reduce maintenance costs, and improve data quality.
Besides BI, modern businesses thrive on effective analytics. A modernized data platform can integrate and extract real-time insights from incoming data (across touchpoints) stored not only in a traditional centralized repository.
As the number of data sources increases, the modernization of traditional data platforms, ETL, and data warehouses
provides the foundation for organizations to achieve business agility. AI-driven replacement for ETL and data warehouses
and BI is bringing great promise for business agility, efficiency, and reaction time without the massive investment in people costs and time to build traditional data pipelines.
Through AI-based modernization, organizations can answer business questions without the traditional need to unify data
from various sources. This helps in eliminating data silos with filtered or limited data sets and minimizing the adoption of
shadow IT because these users have less need to “build their own” analytics solutions. With access to rich AI-enabled data and platforms, business teams can engage in effective analytics – with real-time insights into current business trends and patterns.
With modernization, enterprises can address a common limitation among “traditional” warehouses – lack of scalability. Cloud-powered data and analytics solutions can overcome this limitation with their ability to process diverse data formats at any scale at an affordable cost while unlocking ML and AI capabilities.
Next, let’s discuss the possibilities of how AI technology can transform the data modernization process.
