Магически квадрант BI 2018 – Gartners Business Intelligence

Магически квадрант BI 2018 – Gartners Business Intelligence

Before we examine the maturity model of BI solutions and the guidelines for its development, е необходимо да се извърши анализ на възможностите на BI решения, както и на пазара за тези решения.
As a starting point for this research we take Gartner’s “Magic Quadrants for BI platforms”,

Магически квадрант BI 2018 – Gartners Business Intelligence

In it Gartner defines BI platforms as software platforms providing 12 възможности, разделена на 3 основни категории:
✓ Доставка на информация;
✓ интеграция;
✓ Анализ
Информационни технологии е изключително динамична област на научните изследвания. Като част от него, бизнес
системите за разузнаване (ДА) също се развива много бързо. В тази статия ние ще се придържаме към
следното определение на BIS: "BIS съчетават дейността на извличане на данни и информация
обработка и знания за управление чрез аналитични средства, за да представи
сложна конкурентна информация на потребителите, които черпят планове и да вземат решения. "1
1. Анализ на днешните възможности на BI платформи
Преди да се разгледа модела зрялост на BI решения и насоките за неговото
развитие, е необходимо да се извърши анализ на възможностите на BI решения,
както и на пазара за тези решения.
Като отправна точка за това изследване ние се "Magic квадранти на Gartner за BI
платформи ", публикувано в 2007 (смокиня. 1). В него Gartner определя BI платформи като софтуер
платформи, предоставящи 12 възможности, разделена на 3 основни категории:
✓ Доставка на информация;
✓ интеграция;
✓ Анализ.
1
статии
Към първата категория спадат възможностите за:
✓ доклади Генериране;
✓ навигация стъкла;
✓ Специален заявки;
✓ Интеграция с MS Office.
Втората група включва:
✓ BI инфраструктура;
✓ управление на метаданни;
✓ Разработване на среда;
✓ Workflows;
✓ сътрудничество.
Третата категория обхваща възможностите за:
✓ Онлайн аналитична обработка;
✓ визуализация;
✓ Доставка на знания и прогнозиране;
✓ Карти на резултати.
Пет години по-късно Gartner публикува нов "Магически квадрант за BI платформи",
че все още е на ток за 2012. В този документ BI платформи продължават да се разглежда като
софтуерни платформи, доставяне на възможностите описани по-горе. Но още две функции
Добавени са към категорията "доставка на знания", а именно на базата на търсене BI
и мобилен BI.
Основните възможности на BI платформи са широко дискутирани и изследвани, така поради тази причина те няма да бъдат разглеждани подробно в тази книга. Повече внимание ще
да се обърне на две нови характеристики, предлагана от Gartner.
Първата възможност е базирана на търсене BI. По същество това е приложение на
търсене-индекс на източници структурирана и неструктурирана данни и тяхното делене (организация)
в класификационната структура на мерки и размери, който потребителите могат лесно
навигирате и изследвате, използвайки Google интерфейс, подобен на.
Основната разлика между търсачки и хранилища на данни е, че търсенето
двигатели са много гъвкави и подкрепят всякакъв вид формат и вид информация - било
то структуриран или неструктурирана. Така търсачките могат да се справят с все по-често се развива
структури от данни. Индексирането на съществуващи и нови данни (неизвестен досега) не
изисква допълнително моделиране на данни. Конвенционални съхраняване на данни, архитектура е с ограничена
възможности за справяне с неструктурирани данни, които са необходими за улесняване на решение-
приготвяне и търсачки "запълнят тази празнина". За сравнение, хранилища на данни изискват
време не само за създаването на модела на склад, но също така и за добавяне на нови данни. още
положителна черта на търсачките е, че лесно се "навигация" през съдържание. при
всяка стъпка на навигацията, търсачките предоставят различни възможности за филтриране
резултатите в зависимост от съдържанието на множеството от данни, които са индексирани и
анализирани в почти реално време. Релационни системи за управление на бази данни (RDBMS)
нямам капацитет за анализ на данни, освен ако те притежават някои знания за различни
тип данни. Това е, търсачката може лесно да следите всяко събитие, което се случи на
определен момент, при използване на конвенционални RDBMS за търсене може да се извърши
само в строго определени полета за данни

SAP Business Objects Business Intelligence 4.2 Pack Service 05 BOBJ

SAP Business Objects Business Intelligence 4.2 Pack Service 05 is due to be released at the end of 2o17.

SAP BusinessObjects BI (also known as BO or BOBJ) is a suite of front-end applications that allow business users to view, sort and analyze business intelligence data. The suite includes the following key applications:

  • Crystal ReportsEnables users to design and generate reports
  • Xcelsius/DashboardsAllows users to create interactive dashboards that contain charts and graphs for visualising data
  • Web IntelligenceProvides a self-service environment for creating ad hoc queries and analysis of data both online and offline
  • изследовател — Allows users to search through BI data sources using a GUI interface. Users do not have to create queries to search the data and results are shown with a chart that indicates the best information match.

Тази версия се очаква да предложи редица нововъведения за потребителите и във фокуса на тази версия е около

  • Enterprise - мащабируемост, множество потребители
  • ловкост
  • Смарт стълб - не просто погледнете предварително форматирани съобщения, интегриране с прости предиктивни възможности
  • Big данни - HANA Vora
  • Cloud - инвестиране в "всичко в данните" в облака
  • Hana integration with Hadoop

SAP Business Objects Business Intelligence 4.2 Pack Service 05

SAP Business Objects Business Intelligence 4.2 Pack Service 05

SAP S4 Hana BI Big Data Enterprise Cloud Архитектура

SAP HANA platform has been available since 2010, and SAP applications like SAP ERP and the SAP Business Suite have been able to run on the SAP HANA database and/or any other database since launch.

The SAP S4 HANA platform was released on in February 2015 and SAP S4HANA was billed as being SAP’s biggest update to its ERP strategy and platform in over two decades.

The feedback from analysts was that it was perceived as a transformational shift but raised questions about the functionality, availability, pricing and migration surrounding SAP S4 HANA.

SAP S4 HANA

By the end of 2016, SAP announced that 5,400 customers had implemented SAP S4 HANA but other analysts disputed the viabiltiy of some of these figures given that it included many customers who were actually running Proof of Concept / trial projects rather than customers that were actually live.

Although many SAP customers have heard of HANA SAP still faces challenges getting the user base to understand what the various options are for migration and implementation.

SAP S4 HANA is basically SAP’s well known ERP in the cloud and is powered by the HANA in-memory database and the cloud version of S/4Hana is designed for hybrid scenarios combining on-premises and cloud software.

 

Жълти BI Последни версии

Жълти BI Последни версии

Жълти BI Последни версии – Yellowfin BI is a business intelligence software application that provides a range of Business intelligence dashboard reporting and data analysis functionality. Yellowfin BI allows reporting from data stored in relational databases, multi-dimensional cubes or in-memory analytical databases.

YellowFin BI is based in Headquartered in Melbourne, Australia,

The latest version of жълти BI is 7.3+plus build 20170608 – released on 30 юни 2017

Yellowfin BI Latest Versions

YellowFin BI Version History

Yellowfin BI Version 6.2
Yellowfin BI Version 6.3
Yellowfin BI Version 7.0
Yellowfin BI Version 7.1
Yellowfin BI Version 7.2
Yellowfin BI Version 7.3
Yellowfin BI Version 7.3 Plus

 

 

 

 

Tableau Hyper Двигател Дата на издаване Преглед

Tableau Hyper

Tableau HyperTableau acquired Hyper in March 2016. Hyper was a German, academic based startup developing a high performance, in memory optimal database engine.

Hyper’s high-performance database system is being integrated into Tableau’s product offerings and will bring a range of of new capabilities to Tableau customer base. Hyper will replace the ageing маса Data Engine (TDE).

Tableau Hyper Data Engine

This new functionality will enable existing Tableau users to undertake

  • Faster analysis of Tableau data-sets
  • Improving Tableau’s big data strategy by providing support for large unstructured data sets
  • Improved data integration, data transformation, data aggregation and data blending
  • Richer analytics, such as k-means clustering and window functions
  • Tableau Hyper will also extend the hybrid data model.
  • Unification of analysis and transactional systems
  • Hyper will also provide tools for the harmonisation, cleansing and transforming complex and large data sets
  • The aspiration is that Hyper provides a so-called “instant analytics” capability that will automatically display various contextual details as users interact with their data. This will be served by the in memory processing database engine.

Hyper will also retain connectivity to the 50 or so data sources that Tableau supports in version 10 – this covers disparate data source such as Amazon Redshift, Google BigQuery, Snowflake, и SQL 2017 server.

Tableau Hyper
Tableau Hyper Release Date

The beta for Hyper is already underway (early 2017) and the Tableau Hyper Release Date is expected to be Q4 2017 and be released with версия на маса 11. Hyper will replace the Tableau Data Engine (TDE) by end of 2017.

QlikView Version 13 Дата на излизане

QlikView 13

Business across the globe are evolving at a breathtaking pace and the need to make decisions instantly has also grown multi-fold. Decision making at the Top Executive level is no more an intuitive or hunch-driven thought process. It has to be backed with data and based on data and thorough information. To quickly assimilate a huge amount of data, there is now huge demand for Business Intelligence tools that can help the Top Executives give a quick snapshot of the complete picture of Business. These tools are nowadays an utmost necessity as they help the Management keep an eye on the pulse of the business.

There is a huge gamut of BI tools that are there in the market today which help Business in one or other way. Gartner’s Magic Quadrant has ranked Qlikview Version 13 in the Leader’s segment in the BI products category and Qlikview has been able to maintain its stance for past several quarters which is enough of a reflection of Qlikview’s popularity among the major CIOs of the world from almost all the domains including Finance, Banking, Insurance/Actuaries, Automobiles, Pharma, FMCG, Retails, CPG, Manufacturing, Utilities, и т.н..

 

Ease of Learning Qlikview Version 13

QlikView Version 13 popularity can be attributed to the large number of features that it offers. Not only it has a low deployment time its TCO (Total Cost of Ownership) is also lower compared to several other BI tools. It is easy to learn Qlikview as it has a low Learning curve and also is very easy to be followed and understood for the end user. Since most of the companies/organizations are deploying Qlikview to serve their Data Visualization and Business Analysis needs there is huge Demand Supply gap in terms of required manpower with the desired skillset. Qlikview Developers are having a very absorption rate in the Analytics industry which is no more a strong hold of the big IT firms as it was the case earlier. Every kind of Business be it small, medium or a large enterprise is looking for manpower which can take care of Qlikview setup, prepare dashboards, and prepare business reports for them. Накратко, the demand for Qlikview developers is at its peek at the moment and is a promising field for people who want to enter the Data Visualization arena today.

 

прогнозен анализ

прогнозен анализ ще помогне на вашата организация да разкрие и прогнозират тенденциите, предвидим бизнес климата, и вземане на кола моаре емпирични стратегически решения с помощта на набор от прогнозен анализ софтуер.

прогнозен анализ може да се използва, за да опише всеки подход за извличане на данни с пет атрибути:

  1. предвиждане (а не описание, класификация или групиране),
  2. Гъвкави и бърз анализ измерва в часове или дни
  3. Силно бизнес съответната например. защо ние продаваме х много джаджи в Ню Йорк (не комплекс кула от слонова кост анализи)
  4. Лесен за използване
  5. Силно визуални аналитични резултати (не сложни таблици / данни)

 

прогнозен анализ

В нашия опит на пътя, за да успее с прогнозен анализ е да се дадат повече права на C-Level прогнозен анализ шампион. Напоследък сме работили с голяма организация на дребно с главен финансов директор, който е бил изключително запален по прогнозен анализ, за ​​да помогне за развитието на бизнеса с кола и място на нови пазарни възможности.

 

TIBCO Spotfire Cost – Опции и ценообразуване

Spotfire Costalong with many other software applications it can be quite difficult to find out the cost of the Spotfire Business Intelligence tool.

TIBCO Spotfire designs, develops and distributes in-memory analytics software for use in business intelligence and analytics and provides users with executive dashboards, data analytics, data visualization, ..

tibco spotfire costs pricing

Spotfire has been around since the early 90s but didn’t really take off until 2007, when the brand was acquired by TIBCO Software. An exact customer count is unavailable, and has around $1 billion in revenue and a growing market share of the BI Tools market.

If you are a corporate user then it’s likely you will be able to negotiate a tailored pricing plan depending on the pleothora of different options to choose from.

However to give a flavour for the cost of TIBCO Spotfire Cost there are two potential options

1. Spotfire Cloud Personal Serviceapprox. $300/year, 100GB storage, 1 author seat (slightly limited functionality in that the desktop software has limited connectivity to local data and can upload only local DXP files).

2. Spotfire Cloud Work Group ($2000/year, 250GB storage, 1 business author/1 analyst/5 consumer seats) and gives the single author the ability to read 17 different types of local files (dxp, stdf, sbdf, sfs, xls, xlsx, xlsm, xlsb, csv, txt, mdb, mde, accdb, accde, sas7bdat,udl, log, shp), connectivity to standard Data Sources (ODBC, OleDb, оракул, Microsoft SQL Server Compact Data Provider 4.0, .NET Data Provider for Teradata, ADS Composite Information Server Connection, Microsoft SQL Server (including Analysis Services), Teradata and TIBCO Spotfire Maps. It also enables author to do predictive analytics, forecasting, and local language scripting).

TIBCO Spotfire® Cloud TIBCO Spotfire® Platform
Pricing $200/month OR $2000/annual
subscription pricing
Subscription, Perpetual and Term Licenses
Licenses 1 Authoring Seat (includes online and offline authoring) Per Customer Order
Cloud Data Storage 250GB 0GB

TIBCO Spotfire версия 6 преглед

TIBCO Spotfireis a Data visualisation and anayltics tool that enables users to access, analyze and create dynamic reports on a variety of data sources.

Spotfire, in my opinion is a tool best aimed at those users who are true Data Analysts or using the new buzzordData Scientists“.

Spotfire also keeps the Total Cost of Ownership low by allowing users to build once and publish to many (non licensed) users over internet/intranet, as PDF or as MS PowerPoint reports.

If used correctly with a good all round understanding of the data content Spotfire can deliver immediate value whether you are a market researcher, a sales representative, a scientist or a process engineer by letting you quickly identify trends and patterns in your critical business data.

Spotfire can access data in a number of places such as on your desktop or in a network file system. It can even access your data if it is located in remote databases via the Information Link feature, without you having to involve your IT department each time you wish to ask a new question. However for typical business users most will need input from their IT Departments to make the underlying database tables and fields understanddable. For example making Table 123_xyx / Field 4455gt to beSales Quantity”.

Spotfire lets you filter your data interactively, and helps the business user delve into the data to provide answers instantly and in a visual and understable formatthe old adage of aa picture is worth a thousand wordsand nowhere is this more true than in the case of Data Analytics.

По време на нашето Spotfire Review we were able to create a variety of colorful visualizations in the form of motion charts, bar charts, cross tables, scatter plots and many more that

Spotfire also has a number of nifty features and dashboards with street-level mapping very similaur to Google Maps.

In a recent presentation I was in to the CFO of a Global 100 retailer he stated that he now wanted his team going forward to ditch the Powerpoint presentation and present data to him using Spotfireclearly an enthusiast for this type of tool!

Static reports can be limiting to business users hence Spotfire Version 6 allows you to create dynamic reports that aid the user in posing further business questions and data dissemination. Data visuations can be easily turned into your reports to show to colleagues and customers.

The new features available in Spotfire v6 are:

  • Advanced level Google maps style mapping and integration
  • The ability to interactively select a data subset on a chart and then drill down / through into the data
  • A range of new charts features
  • Text can easily be placed on top of images
  • Improved integration and ability to push data onto mobile devices
  • Visualize, explore and analyze data in the context of location
  • Expand situational understanding with multi-layered geo-analytics
  • Mashup new data sources to provide precise geo-coding across the enterprise
  • Improved Web Based authoring

The Data sources that Spotfire Version 6 can connect to are:

• Cloudera Hive CDH4, CDH5
• Cloudera Impala CDH4, CDH5
• Composite Information Server (ADS) 6.1, 6.2
• Hortonworks Data Platform 1.3, 2.0
• HP Vertica 6.1
• IBM Netezza 6.1, 7.0
• Microsoft Analysis Services 2008, 2012
• Microsoft SQL Server 2005, 2008 R2, 2012
• MySQL 5.1, 5.5, 5.6
• Oracle and Oracle Exadata (Oracle 11gR1 and R2)
• Oracle Hyperion Essbase 9.3, 11.1
• Pivotal Greenplum 4.1, 4.2, 4.3
• Pivotal HAWQ
• PostgreSQL 8.4, 9.0, 9.1, 9.2
• SAP HANA SPS6
• SAP NetWeaver Business Warehouse 7.0.1
• Teradata Aster 5.0, 5.11
• Teradata 12.10, 13.00, 13.10, 14.00, 14.10

Какво е учен данни?

Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science. It incorporates varying elements and builds on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, computer programming, statistics, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Data science is a buzzword, often used interchangeably with analytics or big data, that is often abused for marketing anything involving data processing, in particular to re-brand existing competitive intelligence and business analytics approaches. Data Science need not be always for big data, however, the fact that data is scaling up makes big data an important aspect of data science.

A practitioner of data science is called a data scientist. Data scientists solve complex data problems through employing deep expertise in some scientific discipline. It is generally expected that data scientists are able to work with various elements of mathematics, statistics and computer science, although expertise in these subjects are not required. въпреки това, a data scientist is most likely to be an expert in only one or two of these disciplines and proficient in another two or three. This means that data science must be practiced as a team, where across the membership of the team there is expertise and proficiency across all the disciplines.

Good data scientists are able to apply their skills to achieve a broad spectrum of end results. Some of these include the ability to find and interpret rich data sources, manage large amounts of data despite hardware, software and bandwidth constraints, merge data sources together, ensure consistency of data-sets, create visualizations to aid in understanding data, build mathematical models using the data, present and communicate the data insights/findings to specialists and scientists in their team and if required to a naive audience. The skill-sets and competencies that data scientists employ vary widely. Data scientists are an integral part of competitive intelligence, a newly emerging field that encompasses a number of activities, such as data mining and analysis, that can help businesses gain a competitive edge.

Data science techniques impact how we access data and conduct research across various domains, including the biological sciences, medical informatics, social sciences and the humanities.