In this era of big data, data warehouses have become an important source of business insights.
What is Data Warehousing, exactly?
Data warehousing involves the storage of a large amount of information. Similar to a physical warehouse, which stores physical goods or raw materials, a data warehouse is a repository for data. The purpose of data warehousing is to store of large and complex datasets to easily facilitate the use of data analytic technologies to make sense of business data.
Data warehousing evolved from the need to deal with increasing amounts of data and more complex computing. Invented by IBM’s Barry Devlin and Paul Murphy in 1988, the purpose of data warehousing is to collect structured data from one source or many sources so that the data can be compared and analyzed to help a business gain deeper insights into the performance of their company. Typically, data warehouses store large amounts of data to help companies correlate large amounts of different types of data to develop better business strategies.
How is Data Warehousing different from a database?
A database is a system that is used to monitor and update data, in order to have the newest data available (e.g., to best serve the company’s customers). For example, companies may have a database which contains their customers’ names as well as other information such as the customers’ current addresses. The information in the database is used to help the company meet the customer’s needs more quickly and efficiently.
A data warehouse, by contrast, collects data in large quantities over a period of time. While a database may only have a customer’s current address, a data warehouse may keep records of the customer’s addresses going back 20 years.
Databases and data warehouses are designed differently because they are designed to meet different needs. Databases make storage of customer information more efficient and convenient. Data warehouses are designed to provide a long-range view of data over time -- to help determine the prioritization of products or even customers based upon LTV (lifetime value) or the location of a new company site, for example.
What are the advantages and disadvantages of a data warehouse?
There are many advantages to data warehousing. Data warehousing enables the storage of vast repositories of data. This facilitates advanced business analytics, which results in improved decision making. Data warehousing also enables the consolidation of data from a variety of different sources. Maintaining a dedicated data analytics and data processing warehouse – separate from transactional databases, for example -- also promotes data quality, consistency, and accuracy. This improves the performance of both transactional and data analytic systems.
The disadvantages of operating a data warehouse might include the maturity or preparedness of a business to make the most of the asset or it might be the fact that warehousing isn't ideal for raw, unstructured, or complex data.
Data warehousing can be an important tool as a source of decision-making insights; however, investing in a data warehouse might need buy in from organizational leaders and need a culture change before maximum benefit can be attained. Its imperative to have a business focused executive sponsor to tie the investment of the warehouse to overall organizational goals.
The team at Cruz Street is well equipped to help by providing a "CDO on Demand" or essentially a fractional executive service who's job is to audit data, technology, and people at your organization necessary to execute the strategy you want. Our team will help you both with a strategic road map and with data architecture, data acquisition, solution negotiation and more. Contact us today for an expert consultation!