Five Critical Reasons To Move Your Legacy Data Warehouse To The Cloud
Over 25 years ago, the average business was just becoming acquainted with how to effectively capture and store its data. Back then, data was used to help retail companies manage their inventories, enable commercial airlines to effectively maintain their flight schedules, and allow service-oriented businesses to capture and store their customer contact information. The pace was slower, and the information systems used to compute silo data queries were capable of delivering on time and on-premise.
Today, the entire data infrastructure is no longer scalable, efficient or effective. The introduction of digital communications pushed all past computing paces into warped speeds, forcing IT to operate under extreme pressure in order to meet the demands of today’s consumers. Furthermore, e-commerce and social media are rapidly changing how consumers purchase goods and services — and how they interact with companies. As a result, organizations are witnessing a surge in customer data coming from multiple sources and are flooded daily with a massive amount of data.
Initially, organizations were excited about big data. However, with the information being so abundant and unstructured, it became too large and costly for a traditional infrastructure to manage and store. Furthermore, attempting to analyze and organize the data is too cumbersome.
Cloud Data Warehouse
Today, innovative companies are operating through the use of data science and analytics, and both comprise the future road map for every organization to grow. Running critical analytics under disparate data silos or even small sample datasets will not provide a business with accurate or comprehensive insights. Big data analytics requires a cloud-based infrastructure that can store, manage and compute high volumes of data in order to provide valuable predictions to all employees of a company.
Since data is ingested from various silos throughout an organization, it is important for each business unit to have access to and be able to reference the entire dataset (at a minimum, five to 10 years of data) to garner a true enterprise view of the company’s health in order to resolve a particular situation or pain point or achieve a particular area of growth. Cloud data warehouses have the unique ability to only provide access to data to those users who are granted permission. This way, all company data is protected and secure.
Move To The Cloud
Companies that struggle with gaining the benefits from their big data and disparate silos are at risk of becoming extinct. To become data-centric, stakeholders must be able to understand their current situations through a cloud-enabled holistic view of their company’s data.
The top five reasons to move to a cloud data warehouse are as follow:
1. Cost Reduction: Moving to a cloud data warehouse presents significant savings on hardware, infrastructure and other expenses that come from traditional systems.
2. Improved Profitability: By improving the way data has been collected and processed, you can enable much faster insights on that data.
3. Sales Projections: With the data centralized in the cloud data warehouse, it’s easier for a data analyst or data scientist to build analytics and get actionable insights from that data.
4. Standardize Processes: By enabling your cloud data warehouse and centralizing your data, your data professionals can work together more efficiently. Data professionals from different teams can now perform real-time updates and see what other team members are working on. This level of collaboration between teams can improve the productivity of your projects, as well as your customer service initiatives. Your warehouse will also be dynamic and able to support any scale of workload.
5. Improve Efficiencies: Running analytics on the centralized data in the organization provides you with lots of insights that may highlight gaps that have been impacting the growth of your organization.
Many organizations may think that choosing the right cloud or data warehouse provider is the first step in a data migration project; however, the first step is actually understanding your current IT infrastructure and its capabilities. Performing an architectural evaluation, which is an in-depth analysis of your company’s current technological systems and its capabilities, will provide insights into your infrastructure’s ability to scale and what tools are compatible. The evaluation defines the quality of your current systems and will help you better identify the tools you need for a successful migration.
After your architectural evaluation is complete, you can then begin examining which migration tool and method is the best for your company. Executives across all the industries are now recognizing the advantages of leveraging the cloud data warehouse systems — you may just find your company would benefit from a similar migration.