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How Smart Data Tools Overcome the Challenges of the Data Lake

By   /  October 21, 2015  /  No Comments

lakeby Angela Guess

Marty Laughlin of Cambridge Semantics recently wrote for Inside Big Data, “New smart data tools are rapidly overcoming the common challenges presented by the newly emerging data lake. These tools make it easy to semantically link, analyze and manage diverse data, structured and unstructured, at big data scale and to make it available for self-service consumption by business users. Data lakes are usually defined as large repositories of data, stored in native format and hosted on commodity hardware. Their appeal lies in the ability to rapidly assemble large volumes of unfiltered data and to store it cheaply relative to traditional data warehouses… Following are five key capabilities critical to “democratizing” your data lake project to make it accessible and usable for all business users.”

Laughlin goes on, “A common way to transform and harmonize your enterprise data, regardless of its source, structured or unstructured, inside or outside the enterprise. Driven by the semantic model, scalable servers can convert data from all formats, structured and unstructured into an RDF graph format. An appropriate number of servers may be deployed to accommodate the number of sources and total volume of incoming data, including automatic incremental updates. Depending on the nature of each of the data sources, one or more of the techniques will apply: (1) Mapping and transformation of structured or tabular data. (2) Text analytics, converting unstructured data to structured graphs. (3) Custom plugins for data sources with APIs or proprietary formats.”

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photo credit: Flickr/ markbradleygregory

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