zoomdata vs tableau

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Inference Engine Jess, racer, Jena

, in addition, it is difficult for users to expand it.It is worth noting that racer, fact, and pellet use the descriptive logic as the theoretical basis,AlgorithmThe tableau algorithm is used. These systems have done a lot of optimization work. Jena is an application development kit for semantic web. It contains comprehensive content, and the inference engine is only part of it. The inference engine provided by Jena is similar to that provided by ra

Four ways to get you through. Data Visualization interface Design

monotonic nature of the raw data will help you think about the relationships between the variables in the system. In addition to starting from the blank data, wait for inspiration to suddenly enter your consciousness. You can also be more positive, by following these great resources to help you uncover interesting associations: An automatic data visualization tool developed by Charted--medium. Design better charts through Google Sheets, illustrator and sketch.

What is Apache Kylin?

Apache Kylin's official websitehttp://kylin.apache.org/cn/-Extensible hyper-fast OLAP engine:Kylin is designed to reduce the latency of billions of data queries on Hadoop-Hadoop ANSI SQL Interface:Kylin provides standard SQL support for most query functions for Hadoop-Interactive query capabilities:With Kylin, users can interact with Hadoop data in sub-second, providing better performance on the same data set than hive-Multidimensional cubes (MOLAP cube):Users can define data models and build cu

Extracting __python based on the German map API and Python's geographical boundary coordinates

as an example, its subordinate urban area has 5 administrative districts, there are 8 counties, explain how the next boundary coordinates output ~ (2) on the code, (beginners python, a lot of grammatical structure is still very unclear, here only for the implementation of functions, code written very vexed, readers PAT) #-*-Coding:utf-8-*-# The first line must have, otherwise the report text Fu Fei ASCII error import urllib2 import NumPy as NP import JSON import pandas as PD from Pandas I

git LFS version control for non-code files such as binaries

Recently See Git lfs article, read the next introduction, is really good, similar to Git, but a little different oh. If you want to track the files, go ahead. git lfs track *.pdf In the past, when we were in Tableau's big files, we were going to use git, but it would be slow, and maybe Git server would be hung up. Git in version code, will be differ, just make changes to the change record, do not know git lfs binary is how to do, perhaps each file saved a portion, this is simple (and git trea

Oracle Enterprise Metadata Management (oemm,oracle Meta data Management) 12.1.3.0.1 has been released

meta-data management is essential in the process of data processing and warehouse construction, OEMM can address a variety of key business and technical challenges in the metadata management process, including how to manage metadata, understand the downstream impact of change data, and OEMM stand out in the browser from a business perspective. In the report, you can display the complete metadata information in the enterprise for analyzing and improving the management of meta data. OEMM builds a

How to deploy Rstudio server on a linux server, configure SQL Server on the ODBC Remote Access win server

deployed. (official deployment Help documentation) To download and install the package: The help document gives a EPEL link (epel:extra Packages for Enterprise Linux), logs on to the Linux server, and downloads the package with root privileges. (wget command Download) Find the package downloads that match your server version, r and Rstudio server's installation package are all inside, and some commonly used Rstudio company developed R packages such as Ggplot2,dplyr and so on are included. Afte

Python and R data analysis/mining tools Mutual Search

R Tokenize Nltk.tokenize (UK), Jieba.tokenize (middle) Tau::tokenize Stem Nltk.stem Rtexttools::wordstem, Snowballc::wordstem Stopwords Stop_words.get_stop_words Tm::stopwords, Qdap::stopwords Chinese participle Jieba.cut, Smallseg, Yaha, finalseg, genius Jiebar TFIDF Gensim.models.TfidfModel Unknown Topic model category Python

The evolution of the Apache Kylin Big data analytics Platform

-threaded algorithm, but Kylin uses a parallel algorithm.User-TOPN queries, such as fetching 100 data, are written as SQL statements as shown in. and Kylin will automatically adapt to such a SQL to directly use the pre-aggregated good results, so at run time Kylin just put the pre-calculated 1000, 10,000 item directly back to the good, there is almost no online calculation, the speed will be very fast.  7. Integration of analysis tools  In the new version, Kylin also added some ODBC interfaces,

Business Intelligence promotes the development of the big data age

the data sources are also diverse. data processing, analysis, and mining and presentation are no longer limited to traditional methods, unstructured massive data needs to be developed and mined urgently. market demands are becoming increasingly popular and technologies are constantly innovating. Distributed Storage and nosql database technologies are continuously developed and applied to data warehouses to achieve scalable massive data storage and high-performance queries, which inspires and su

Tableau10.0 Learning-Grouping problem

1, according to the official website of the practice video, groups can be more than the choice of columns, then use the paperclip button to create a group, and rename it, as follows:2, but in Tableau10 open practice workbook exercise, did not directly display the group results, just create the latitude of the grouping, the result is as follows:3. Using the data source in the workbook and creating a new icon test is still the effect in step 2:4. After testing in the new practice workbook, use the

Data mining engineer Interview Guide

. One reference is to provide a defective analysis report. Allow candidates to study the report, express the meaning of the conclusions in the report, propose existing problems or deficiencies, and propose methods for improvement or remedy.5. ConclusionAt the final stage of the interview, you need to answer other questions from the candidate and trust the company's competitive position in the industry and its role in your career. After completing the interview, you need to archive the interview

Introduction to Baidu data visualization practices for csdn open-source summer camp

First of all, I would like to thank Miss Lin Feng for choosing me. @ Kener-Lin Feng (1) Next I will introduce Baidu's data visualization components echarts and zrender.As we all know, the arrival of the big data era not only brings challenges but also opportunities, but it is only a start. The big data era will have a major impact on our lives. As Victor may-schenberger, author of The Big Data age, said, "Today, data has become a commercial capital and an important economic investment, new econo

Hadoop is more suitable for enterprise applications in the 2.0 age

online memory-based high-speed analysis. Transwarp Data Hub integrates Data integration/ETL, big Data storage and online service systems, memory-based efficient computing engines, high-performance SQL, statistical analysis, and machine learning, achieving Performance breakthroughs. In Sun yuanhao's words, Transwarp Data Hub has a "lightning" speed, which is 10-10 faster than the open-source Hadoop 2.0 ~ 100 times. In addition, Transwarp Data Hub has powerful analysis capabilities and is fully c

Too many choices-how do companies choose the right BI tool?

as SAP BO, Cognos, ORACLEBIEE, etc., self-help BI, such as foreign tableau, Qlikview, domestic finebi, Yonghong bi and so on.From the perspective of the enterprise of the product, we can measure from the leading ability, product ability, service ability and price ability. Can be judged by a set of "BI Selection Index system" given by sea ratio research.1, leading capacity = Industry Status + leadingsuch as the company's low in the industry, market sh

Kylin working principle, architecture

Core idea: expected calculation.Pre-calculates the metrics that may be used for multidimensional Analysis, saves the calculated results to a cube, and exists in hbase for direct access when queriedHigh-complexity aggregation operations, multi-table connections ... The operation is converted into a query for the precomputed results. Determines that Kylin has a very good fast query, high concurrency capabilityTheoretical basis: space Change timeCuboid:kylin any combination of dimensions into a Cub

BI (Business Intelligence)

charges, the use of expensive, 1TB data may need hundreds of thousands of. Such big data products dramatically increase the total cost of ownership (TCO) of BI applications. In today's BI market, new trends are emerging and gaining momentum, such as agile bi and exploratory bi. In the past two years in the United States, two companies Qliktech and Tableau have successfully listed and entered the mainstream market, and in China has emerged in the Yong

Complex reports where is the complexity?

total can not be repeated calculation of the state Government sales). reporting tools after 10 years of development, most of the front-end challenges have been properly resolved, such as Style report,Runqian reports,QlikView, Tableau, each of which solves these challenges in different ways. Now the report is mainly complex in the backend, that is, the calculation of the data source. N Complex business logic. For example: Find salespeople with th

PHP correct use of plural

', -' Memorandum ' = ' Memoranda ', the' Millennium ' = ' millenniums ',//MilenniaBayi' Moose ' = ' moose ', the' Mosquito ' = ' mosquitoes ', the' Mouse ' = ' mice ', -' Nebula ' = ' nebulae ',//Nebulas -' Neurosis ' = ' neuroses ', the' nucleus ' = ' nuclei ', the' Oasis ' = ' oases ', the' Octopus ' = ' octopi ',//Octopuses the' Ovum ' = ' ova ', -' Ox ' = ' oxen ', the' Paralysis ' = ' paralyses ', the' parenthesis ' = ' parentheses ', the' Person ' = ' people ',94' Phenomenon ' = ' phenome

How to Build compelling Stories from Your Data sets

principle-in science, it's a thesis statement.From there you can develop the kernel, and begin to focus on ' minor plot lines ' and other information ' in and of Itsel F may isn't being compelling, but the greater context adds value to the story. That kernel can work in the different ways.Enhance:start Big and Narrow inWhether you ' re using a series of visuals, a graph, a chart, or something completely new and different, you can layer the D Elivery of your information. The first method of laye

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