Concerted is a highly scalable multivariate in-memory data storage library. It has built in support for multivariate queries and performs well over many styles of workloads. The data is read and stored in various data structures, and the data from data structures written to disk. It is fully ACID compliant, has APIs that abstract details from the user, and provides an easy to use interface. Many different types of indexes are provided along with various systems that provide access for data analytics.
statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics. statsmodels was renamed from scikits.statsmodels.
scikits.statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear models, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics.
The CloverETL Profiler, software for data profiling, works to examine data in existing data sources and collect statistical information about said data. Through this process, the profiler eliminates the guesswork in analysis, revealing an understanding of what data actually exists and what needs to be improved. Part of the CloverETL Data Integration family, the Profiler is an added tool to the enhanced toolset. Whether employed as a standalone job or part of a greater project, the CloverETL Profiler, as named, operates with the same Engine as CloverETL, offering high performance, speed, and easy deployment in a data environment.
Cubes is a Python framework for online analytical processing (OLAP), multidimensional analysis, star and snowflake schema denormalization, and cube comptutation. It features a logical model that describes how data are being analyzed and reported, independent of physical data implementation, hierarchical dimensions (attributes that have hierarchical dependencies, such as category-subcategory or country-region), localizable metadata and data localization.
CloverETL is Java-based tool/framework for data integration and creation of data transformations. It is component based and follows the concept of transformation graphs which consist of individual nodes/components performing simple (or complex) operations on data. Any transformation can be defined as a set of interconnected nodes through which data flows. CloverETL can be used as a standalone application or be embedded into a larger project.