Hadoop for the Enterprise - Making Data Management Massively Scalable, Agile, Feature-Rich, and Cost Effective

https://www.cloudera.com/content/dam/cloudera/Resources/PDF/Reports/TDWI-Best-Practices-Report_Hadoop-for-the-Enterprise.pdf

TDWI research paper Hadoop for the Enterprise indicates that Hadoop usage will become mainstream in coming years, and – more to the point – Hadoop will serve whole enterprises, not just a handful of users with niche applications in a limited numbers of industries. The report explains how Hadoop and its uses are evolving to enable enterprise grade deployments that serve a broadening list of use cases, user constituents, and organizational profiles.

In our organization we are developing Hadoop strategy and road map. From Application architecture perspective, we see many opportunities and use cases that can bring business values to the organization.

As UWE LIEBELT, President BASF 4.0, BASF SE said "We must and we will look very carefully at the opportunities and challenges presented to us by digitization. For BASF, the spectrum of possible models ranges from digital chemicals group to market leader for digital business models in chemicals." Following industry 4.0, BASF kicks off BASF 4.0 which will bring a huge opportunity of digitization from digital chemicals group to market leaders for digital business models in chemicals.

BASF Maglis project uses Hadoop to provide data information, data entry and processing, collection, compilation and systemization of data information in databases for customers in regarding to agriculture, horticulture and forestry. IoT (Internet of Thing) will connect manufacturing devices, sensors and systems together, Hadoop will provide a necessary storage and proceeding power for IoT.

Some other use cases are:

Data warehouse extensions – Hadoop can be used as a complementary extensions of a data warehouse when warehouse data doesn’t necessarily require the warehouse is migrated to Hadoop.

Analytics and BI – BI involves data exploration and discovery, which are critical to learning new facts about a business as well as getting to know new big data and its potential business values. To enable the broadest possible exploration, numerous large datasets can be co-located on Hadoop.

Data Lake and Data Hub – Both involve loading multiple massive datasets into Hadoop with little or no preparation of the data. That way, data ingestion is fast, simple, and inexpensive. This can help solving big data challenge for the organization

Predictive maintenance for the chemical manufacturing – a large amount of machines, sensors and systems data can be loaded into Hadoop for analysis and predictive maintenance.

From Application Architecture perspective, Hadoop can optimize organization’s application portfolio, bring more business opportunities and improving organization’s application landscape.