Big data and data management white papers: DBTA maintains this library of recent whitepapers on big data, business intelligence, and a wide-ranging number of other data management topics.
The increasing availability of assays that utilise smaller quantities of source material and produce higher volumes of data output have resulted in the necessity for data storage solutions beyond those previously used. Multifactorial data, both large in sample size and heterogeneous in context, needs ...
for example, to use Big Data to determine how well your sales campaigns perform, but even greater business value is derived when an enterprise can determine not only who became customers but also how valuable those prospects were (i.e., how much they...
SNs continuously generate an enormous quantity of heterogeneous data gathering the most valuable information: user behaviors. This unprecedented amount of data is leveraged by the “Do ut Des” strategy of the big companies (i.e. Amazon
In this study, we explore sample size determination methods for four real-world biomedical datasets, spanning genomics, proteomics, electronic health records, and insurance claims data, all with millions of instances each and<2% class ratio. The methods used involve approximating a learning curve for...
Variety: the variety of data is also diverse, and data can be structured and unstructured from different types, sources, and media. For example, digital astronomy can have large datasets of images and sky survey images, but they are mainly structured data. In comparison, big data from social...
Gnocchi- Gnocchi provides primitives for running GWAS/eQTL tests on large genotype/phenotype datasets using ADAM. Lime- Lime provides a parallel implementation of genomic set theoretic primitives using the ADAMregion joinAPI. Mango- Mango is a library for visualizing large scale genomics data with int...
datasets documentation pictures raha supplementaries .gitignore LICENSE.md MANIFEST MANIFEST.in README.md requirements.txt setup.cfg setup.py README Apache-2.0 license Raha and Her Younger Sister Baran Detecting and correcting erroneous values are key steps in data cleaning. Error detection/correction ...
In detail, we use the canonical polyadic decomposition and the tensor-train network to compress the attributes of each big data sample. To evaluate the performance of our algorithms, we conduct the experiments on two representative big data datasets, i.e., NUS-WIDE-14 and SNAE2, by ...
3.1 Big Data Technology for the Plant Community Big data technology, typically, refers to three viewpoints of the technical innovation and super-large datasets: automated parallel computation, data management schemes, and data mining. Fig. 6 describes main components of the big data technology. The...