By Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao
This e-book has a suite of articles written by means of mammoth info specialists to explain a number of the state of the art tools and purposes from their respective components of curiosity, and offers the reader with a close assessment of the sector of massive info Analytics because it is practiced at the present time. The chapters disguise technical facets of key components that generate and use tremendous information resembling administration and finance; drugs and healthcare; genome, cytome and microbiome; graphs and networks; net of items; large facts criteria; bench-marking of structures; and others. as well as diversified purposes, key algorithmic methods reminiscent of graph partitioning, clustering and finite blend modelling of high-dimensional info also are coated. the various selection of subject matters during this quantity introduces the reader to the richness of the rising box of massive info Analytics.
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Extra info for Big Data Analytics: Methods and Applications
HPCC uses a data-centric, declarative programming language called Enterprise Control Language (ECL) for both data reﬁnery and query delivery. By using ECL, the user speciﬁes what needs to be done on data instead of how to do it. The data transformation in ECL can be speciﬁed either locally or globally. Local transformation is carried out on each ﬁle part stored in a node of the Thor cluster in a parallel manner, whereas global transformation processes the global data ﬁle across all nodes of the Thor cluster.
37 dation (RIR) needs a diﬀerent architecture compared to Similar Items Recommendation (SIR). , biomedical link prediction) process massive graphs as their underlying structure. Distributed graph techniques need to be in place for eﬃcient and timely processing of such structures. , path-based processing in distributed graphs). ∙ Data locality and replication management policies ought to be cleverly integrated to provide robust and fault-tolerant massive data analytics. ∙ As massive data are generally produced from a great variety of sources, novel, semantics-based solutions should be developed to eﬃciently support data heterogeneity.
The reports had to be preprogrammed and were produced at speciﬁed times such as quarterly, half-yearly or annually. With the advent of relational database systems (RDBMS) and the structured query language (SQL) ad-hoc reporting became possible. The managers could query their organisation’s databases to seek information and reports which were not preprogrammed and were not routinely required. The A. in © Springer India 2016 S. Pyne et al. 1007/978-81-322-3628-3_3 41 42 A. Laha ability to query the database and drill-down as and when required allowed managers to ﬁgure out root causes of problems and helped them in eliminating these.