Tips for Enhancing Your Data Lake Strategy
Posted on October 11, 2018
As organizations grapple with how to effectively manage ever more voluminous and varied reservoirs of big data, data lakes are increasingly viewed as a smart approach. However, while the model can deliver the flexibility and scalability lacking in traditional enterprise data management architectures, data lakes also introduce a fresh set of integration and governance challenges that can impede success.
The Power and Potential of Data Lakes
Born from the rise of the cloud and big data technologies like Hadoop, data lakes provide a way for organizations to cost-effectively store nearly limitless amounts of structured and unstructured data from myriad sources without regard to how that data might be leveraged in the future. By its very nature and through self-service business intelligence capabilities, a data lake also encourages experimentation and data exploration by a broader set of non-business analyst users. According to a survey conducted by TDWI Research, 85 percent of respondents considered the data lake an opportunity to address the challenges they face trying to manage the data deluge with traditional relational databases. Moreover, the TDWI survey found the data lake being pursued for a variety of benefits and use cases, the most prominent being advanced analytics (49 percent) and data discovery (49 percent).