Unleashing the next level of organizational decision-making with the cloud data warehouse
The ability for cloud data warehouses to provide a single platform that enables organizations to analyze data at any scale is a market changing capability. Sure, much has been made of the ability of applying Artificial Intelligence (AI) to this data to gain insight into new areas, ultimately to increase an organization’s competitiveness. There is however a greater level of impact that this architecture can have that can be independent of AI and ultimately inclusive of AI.
Nearly every organization has function based organizational silos, such as Sales, Marketing, Supply Chain, and Support to name a few. Traditionally each of these organizations has deployed their own data implementation that is optimized for the specific decisions that functional organization performs. While each of these functional organizations optimizes their particular data-sets, there is very little organizational data, beyond high-level summaries, that ties it all together. This means that cross-functional decisions, which are made in a meeting room, and not through deep understanding of the data, are lacking in factual basis.
The negative impact of this data-architecture and associated decision-making process is that many functional organizations are in conflict with their peers. In the early 2000s Ford was on the brink of going bankrupt, for many reasons, but in particular the manufacturing and sales organizations were in direct conflict with each other. Factories were building new cars at an efficient rate and operating around the clock, but the sales numbers were not keeping up. In fact, many of the cars were being transported to fields for storage, so Ford’s costs were going up. Sales were incentivized to clear these lots and, as such cars were sold below cost, ultimately leading to Ford almost disappearing.
For all of Ford’s investment in data technology, they ultimately did not have the insight to see what was right in front of them. Key to their turnaround was their new CEO, Alan Mulally, who understood the negative impact of functional data silos and defined the problem within the larger On-Ford initiative to turn around te company’s fortunes. Furthermore, Mulally encouraged Ford’s functional organizations to co-operate and make data central to every decision process. In contemporary, or agile based organizations, this moved Ford from decision making based on summary statistics, to being able to traverse the whole organization’s data to perform the 5-whys, and was critical to Ford’s ultimate success.
Finding the answers in the warehouse
5-Whys is a simple technique where a problem or answer is challenged at least five times to understand the root cause and, ultimately, fix the cause not the symptom. For the first time, data warehouses now support this type of decision-making as query scope and performance is not limited to a specific database or a small subset of databases. The challenge now is to rapidly build a data-warehouse that covers as many functional groups within an organization and their related data sources as quickly as possible.
Talend enables this in a number of different ways, ensuring that data from all areas of an organization can be rapidly collected and integrated. Traditional data sources can be rapidly ingested, valiated and made available using Talend’s 2,000 plus connectors and components. Furthermore, Talend partners have built automation systems that quickly understand the problem metadata and generate all the data integration jobs ready for deployment in at least one to two orders of magnitude faster than before.
Foresight is competitive
Other partners go a step further to migrate not only the data, but the associated ETL jobs as well. In addition, for contemporary data-sources that are typically found in the cloud, Stitchdata from Talend can be applied to quickly ingest the Digital, Marketing, Sales, and Customer Success data, the understanding of which is now a key requirement for CROs (Chief Revenue Officers). With this information these executives are able to use and traverse all aspects of their organization’s data and how it impacts the future competitiveness of their organization.
AstraZeneca, one of the largest biopharmaceutical companies in the world utilizes Talend for exactly this purpose. They used Talend to connect data from a multitude of systems in a cloud data lake to improve reporting, regulatory insights and, most importantly, find insights hiding in previously unconnected data sources. According to Simon Bradford, Senior Data & Analytics Engineer at AstraZeneca: “To be able to easily analyse that data, we knew we needed to put in place an architecture that could help with a mass consolidation and bring data together in a single source of the truth.” Talend enabled them achieve these results.