tableau olap

: Deterministic data analysis: mainly simple data statistics tasks, such as OLAP, attention to rapid response, the implementation of components such as Impala; Exploratory data analysis: Mainly information-related discovery tasks, such as searching, focusing on unstructured full-volume information collection, implementing components such as search; Predictive data analysis: Mainly machine learning tasks, such as

running shark. In this architecture, Spark replaces Hadoop as an ETL, while Shark replaces the commercial Bi/olap tool, taking on reports/dashboards and interactive/ad hoc queries, while interfacing with desktop bi tools such as tableau. The current spark cluster deployed on Yahoo has 112 nodes, 9.2TB of memory, and is considering adding SSDs. Tim introduces the future of work. First of all, Pig/mapreduce

A good tool can help you do more, especially in the big data age, where powerful tools are needed to visualize data in ways that make sense. Some of these tools are applicable to. NET, Java, Flash, HTML5, Flex and other platforms, there are also applicable to the general chart report, Gantt Chart, flowchart, financial charts, industrial charts, PivotTable reports, OLAP Multidimensional analysis, such as chart report development, Let's take a look at s

evolve into today's rich and diverse internet. We think that SQL has become the waist of data analysis. In our time of life, data is becoming "the most valuable resource in the world" (The Economist, May 2017). Therefore, we have seen the professional database (OLAP, time series, documents, charts, etc.), data processing tools (Hadoop,spark,flink), Data Bus (KAFKA,RABBITMQ) and so on, showing the Cambrian explosion-like situation. We also have more a

APACHE kylin™ OverviewApache kylin™ is an open-source, distributed analytics engine that provides SQL query interface and Multidimensional Analysis (OLAP) capabilities on top of Hadoop to support hyper-scale data, originally developed and contributed by ebay Inc to the open source community. It can query large hive tables in sub-second.What is Kylin?-Extensible hyper-fast OLAP engine:Kylin is designed to re

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 cu

processing structure, new data organization, query strategy, indexing technology and so on. Many applications, including online analytical processing (On-line Analytical processing, OLAP), drive the emergence and development of data Warehouse technology, and the Data Warehouse technology, in turn, promotes the development of OLAP technology. The concept of online analytical processing was first proposed b

Summary Many organizations use Online Analytical Processing (OLAP) technology to analyze their key business data. OLAP-based data Drilling provides a way to query multi-dimensional datasets and obtain modes through drilling data. ASP. NET and Microsoft Office Web Components (owc) Enable Web-based OLAP reports. The owc control can be embedded on web pages andPro

Kylin using the installation documentationKylin IntroductionWhat is Kylin?Apache Kylin is an open source distributed analytics engine that was originally developed by ebay to contribute to the open source community. It provides SQL query interface and Multidimensional Analysis (OLAP) capabilities on top of Hadoop to support large-scale data processing, with the ability to handle terabytes and even petabytes of analytic tasks, to query large hive table

memory data storage for real-time operational analytics, providing data flow analysis, OLTP (online transactional processing), and OLAP (online analytics processing) built into spark single integrated clusters;　　Snowplow: Enterprise-Class networking and event analytics with technical support from Hadoop, Kinesis, Redshift, and Postgres;　　Sparkr:spark R front-end;　　Splunk: Analysis of data used in machine generation; Sumo Logic: Cloud-based analyzers

the presentation and application tiers in most organizations. For example, BI tools Finebi provides data integration, data cleansing (ETL) to data caching and final data presentation and front-end analysis, as well as mobile, large-screen solutions, from the underlying data to the front-end presentation.The use of BI in enterprise data decision-making is nothing more than the following.1. What happened in the past?By consolidating the existing data of the enterprise, it is presented in the way

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

data analysis.We live in a time when data is becoming "the most precious resource in the World" (""Economist", May 2017). We saw Cambrian's professional database (OLAP, time series, documents, charts, etc.), data processing tools (Hadoop,spark,flink), the data Bus (KAFKA,RABBITMQ) and other Red Sea. There are more applications that need to rely on this data infrastructure, whether it is a third-party data visualization tool (

federate multiple data sources. Users can submit queries through C, Java, node. js, PHP, Python, R, and Ruby. Airpal is a Web-based query tool developed by Airbnb that allows users to submit queries to Presto via a browser. The Qubole bit Presto provides management services. AWS provides Presto services on EMR. In June 2015, Teradata announced plans to develop and support the project. Based on the announced three-phase plan, Teredata proposes to integrate Presto into the Hadoop ecosystem, to op

announced plans to develop and support the project. Based on the announced three-phase plan, Teredata proposes to integrate Presto into the Hadoop ecosystem, to operate in yarn, and to enhance connectivity through ODBC and JDBC. Teredata offers its own Presto release, with a data sheet attached. In June 2016, Teradata announced the results of information Builders, Looker, Qlik, Tableau and Zoomdata, as well as ongoing microstrategy and Microsoft Powe

Bi-open the door to Business IntelligenceTo meet the requirements of enterprise managers, a Bi system must take the following steps:1) to integrate data in various formats, clear the error records in the original data-data preprocessing requirements.2) data pre-processing should be centralized in a unified manner-metadata (metaDaTa, data warehouse (DA)TaWarehouse) requirements;3) Finally, professional statistics should be made on a large centralized dataset to discover new opportunities that are

personal opinions on data analysisAfter doing the data Product manager, has done some simple homework to the data analysis work, now records as follows, hoped can help the data product aspect schoolmate, simultaneously also takes this platform to exchange the study, the improper place, also please treatise. Data Product Manager ResponsibilitiesData analysis--grasping data dynamics, the value behind the pivot data---------------------------------------------------------------- See the article i

):Tn.write (command[i]+ ' \ r \ n ')Res=tn.read_until (">")Winres=res.decode (' Utf-8 '). Encode (' Utf-8 ') # ' \xe5\xb7\xb2\xe5\xae\x8c\xe6\x88\x90 'Print WinresSuccon= ' Backup written 'If Succon in Winres: #9print ' Success 'Tn.write (' exit\r\n ')Tn.close ()Elseprint ' fail 'Tn.write (' exit\r\n ')Tn.close ()Sys.exit (1)Def get_workbook ():Logpre=time.strftime ('%y-%m-%d ', Time.localtime (Time.time ()))command170=[' CD c:\\program Files\\tableau

This is a created article in which the information may have evolved or changed. Recent tasks have been a bit busy, mainly in the data analysis needs of various departments, coupled with the app backend performance optimization squeeze together. The previous data-related work was mostly passive, and each department gave the data analysis requirements, and then a person analyzed the data from ES or Hadoop, and finally drew it with tableau, then expor

Four types of BI open source tools introduction-spagobi,openi,jaspersoft,pentaho1 Brief Introduction to BI systemsFrom a technical point of view BI includes ETL, DW, OLAP, DM and other links. Simply put, the transaction system has already occurred data, through the ETL tool extracted to the subject of a clear data warehouse, after the OLAP generation cube or report, through the portal to show users, users u