Date Lake and Data Warehouse are designed and used for different purposes: the data lake is an excellent solution for analytics, but it is not suitable for the interaction between the different operating systems.
According to Martin Fowler: “The lake is too complex to trawl for operational communication. The analysis of the lake could possibly lead to new operational communication routes, but these should be built directly rather than through the lake”.
It is the technology that has to adapt to the organizational model and not vice versa: the Data Warehouse, in particular through the hub and spoke model, has been optimized for this reason. Many companies are choosing it because it best fits their specific needs, and because the hub-and-spoke model allows organizations to analyze and process more forms of data, and it saves money by removing the need for capital intensive data warehousing infrastructure.
Adopting a “hub and spoke” architecture for information systems can help organizations maximize the value of their data, according to a new report from Forrester Research.
With the data warehouse, the data is periodically extracted from applications that support the business processes and replicated on dedicated computers. The data can be validated, revised, re-sorted, summarized and integrated with other data from other sources, and so used as an information base for reporting and analysis.
Furthermore, if the data are not used in requests or specific reports, they may be excluded from the archive. This serves to simplify the data model and not wasting any space left on the HDD and use it better to improve the data warehouse performance. In addition to reducing costs, the hub and spoke system does not lose its original characteristics and thus protects the investment, being a commodity: Commodity, off-the-shelf servers combined with cheap storage makes scaling a lake to terabytes and petabytes date fairly economical.
Now, with RB1 of Radicalbit, organization business units can now take advantage of modern and advanced Fast Data technologies, by developing vertical implementations without interfering but actually integrating with a broader enterprise data hub vision. It is an architecture-based system hub and spoke, and who can meet the needs of autonomy, flexibility and agility of the individual business units. It’s flexibile because unlike traditional relational databases, you don’t have to preprocess data before storing it. You can store as much data as you want and decide how to use it later. That includes unstructured data like text, images and videos. Also it allows you to move with a certain agility in business requirements, with respect to the date lake mechanisms, by standardizing the integration paradigm, hub-spoke architecture increases your ability to adapt your business. Adding new marketplaces and new sales channels become far simpler. They require less time, less investment, and less risk. This helps you move quickly.