As a critical component of informed decision-making, asset managers have become increasingly reliant on data to help them grow their business, especially in today’s ever-evolving and competitive landscape. With this, firms require a warehouse to help them handle data’s exponential expansion of availability and use cases – leaving many to question whether they should stick with a traditional solution or migrate to a cloud data warehouse solution.
A Traditional Solution
Traditional solutions are on-premises data warehouse that require the provisioning of local IT server resources to deliver the warehousing solution. Asset management firms running on-premises enterprise data warehouse solutions also need to manage the underlying infrastructure of the warehousing platform. These traditional data warehouses are usually built on a multi-tier structure, as described below:
- Bottom Tier: This layer is used to extract data from a range of sources. It contains the actual database server used to remove data from sources and integrates it into a single repository.
- Middle Tier: This layer houses the online analytical processing (OLAP) server. It processes the complex queries to present results in a form suitable for data mining, analytics and business intelligence.
- Top Tier: This layer acts as a client interface and houses the front-end BI tools used for querying, reporting and analytics.
These on-premises legacy data warehouse solutions are still proficient at integrating structured data and business analytics in some form, but they lack the ability to handle diverse, massive amounts of data analytics and ramp up processing when required. Furthermore, on-premises means additional layers of overhead cost when updating and maintaining the underlying infrastructure.
A Cloud-Based Solution
A cloud data warehouse solution aims to overcome the limitations of a traditional warehouse solution. While the two types of platforms differ in their actual implementation and management of resources, the overall idea and problems to be solved remain the same. They are both engineered to handle all types of data, manage unique workloads and perform advanced analytics, but a cloud data warehouse solution provides firms with a number of benefits that a traditional solution lacks, such as:
- Cost Savings: Since this solution does not require physical hardware, maintenance, and upgrades, it essentially reduces the cost of ownership while providing the flexibility to use a pay-as-you-go model and easily adapt to the evolving needs of the firm.
- Scalability: The elastic resources of the cloud make it ideal for scaling quickly and inexpensively. Additionally, cloud data warehousing options can also scale down as needed, which is challenging with other approaches.
- Flexibility: Designed to account for the variety of formats and structures of data, these solutions are suited to process complex datasets with both ease and efficiency.
- Access: Data stored in a cloud data warehouse solution can be accessed and analyzed quickly with the ability to provide real-time insights, all while reducing decision-making time.
- Maintenance: Since these types of solutions are not hosted on-premises, the level of involvement in maintenance, upgrades and troubleshooting activities in case of a failure is reduced. Also, cloud data warehouse solutions provide the ability to easily monitor systems from anywhere for efficient workflow.
IVP Data Warehouse is strongly positioned to integrate with all industry-leading cloud data warehouse solutions, providing firms with the ability to deploy as an enterprise solution when required. It features integrated modules that are enhanced with strategy-aware dashboards, optimized workflows, advanced performance tracking capabilities, and streamlined reporting and analytics capabilities, thereby equipping firms with predictive insights for more strategic decision-making.
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Our cloud data warehouse solution makes it easy to collate, cleanse, enrich, and manage enterprise data from internal systems, fund admins, brokers, and third-party systems for performance reporting, analytics, and more.
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