SAP Business Objects Business Intelligence 4.2 सेवा संकुल 05 BOBJ

SAP Business Objects Business Intelligence 4.2 सेवा संकुल 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
  • ExplorerAllows 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.

This version is expected to offer a number of innovations to users and the key focus of this release is around

  • Enterprise – scalability, multiple users
  • Agility
  • Smart pillar – not just look at preformatted reports, integrating with simple predictive capabilities
  • Big data – HANA Vora
  • Cloud – investing in “all in data” in the cloud
  • Hana integration with Hadoop

SAP Business Objects Business Intelligence 4.2 सेवा संकुल 05

SAP Business Objects Business Intelligence 4.2 सेवा संकुल 05

एसएपी एस 4 हाना बीआई बिग डाटा उद्यम बादल वास्तुकला

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.


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.


YellowFin BI Latest Versions

YellowFin BI Latest Versions

YellowFin BI Latest VersionsYellowfin 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 Yellowfin BI is 7.3+plus build 20170608 – released on 30 June 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 Engine Release Date Review

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 Tableau 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, तथा एसक्यूएल 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 संस्करण टेबल 11. Hyper will replace the Tableau Data Engine (TDE) by end of 2017.

जादू चक्र बीआई 2018 – Gartners व्यापार खुफिया

जादू चक्र बीआई 2018 – Gartners व्यापार खुफिया

Before we examine the maturity model of BI solutions and the guidelines for its development, यह बीआई समाधान की क्षमताओं का एक विश्लेषण करने के लिए आवश्यक है, साथ ही इन समाधान के लिए बाजार.
इस शोध के लिए एक प्रारंभिक बिंदु के रूप में हम बीआई के लिए गार्टनर की 'जादू चतुर्भाग ले
प्लेटफार्मों ",

जादू चक्र बीआई 2018 – Gartners व्यापार खुफिया

इसमें गार्टनर सॉफ्टवेयर के रूप में बीआई प्लेटफार्मों को परिभाषित करता है
उपलब्ध कराने के प्लेटफार्मों 12 क्षमताओं, में विभाजित 3 बुनियादी श्रेणियों:
✓ जानकारी की डिलिवरी;
✓ एकता;
✓ एनालिटिक्स
सूचना प्रौद्योगिकी अनुसंधान के एक अत्यधिक गतिशील क्षेत्र है. यह के भाग के रूप, व्यापार
खुफिया प्रणाली (करने के लिए) भी बहुत जल्दी से विकसित. इस पत्र में हम का पालन करना होगा
बीआईएस के निम्नलिखित परिभाषा: "बीआईएस डाटा खनन और डेटा की गतिविधियों गठबंधन
आदेश में पेश करने के लिए विश्लेषणात्मक साधनों के माध्यम से प्रसंस्करण और ज्ञान प्रबंधन
उपभोक्ताओं को योजनाओं आकर्षित और निर्णय लेने के लिए जटिल प्रतिस्पर्धी जानकारी। "1
1. बीआई प्लेटफार्मों की आज की क्षमताओं का विश्लेषण
इससे पहले कि हम बीआई समाधान की परिपक्वता मॉडल और के लिए दिशा निर्देश की जांच अपने
विकास, यह बीआई समाधान की क्षमताओं का एक विश्लेषण करने के लिए आवश्यक है,
साथ ही इन समाधान के लिए बाजार.
इस शोध के लिए एक प्रारंभिक बिंदु के रूप में हम बीआई के लिए गार्टनर की 'जादू चतुर्भाग ले
प्लेटफार्मों ", में प्रकाशित 2007 (अंजीर. 1). इसमें गार्टनर सॉफ्टवेयर के रूप में बीआई प्लेटफार्मों को परिभाषित करता है
उपलब्ध कराने के प्लेटफार्मों 12 क्षमताओं, में विभाजित 3 बुनियादी श्रेणियों:
✓ जानकारी की डिलिवरी;
✓ एकता;
✓ एनालिटिक्स.
पहली श्रेणी के लिए के लिए क्षमता से संबंधित:
✓ उत्पन्न रिपोर्ट;
✓ नेविगेशन फलक;
✓ तदर्थ प्रश्नों;
✓ एमएस ऑफ़िस के साथ एकीकरण.
दूसरे समूह में शामिल हैं:
✓ बीआई बुनियादी ढांचे;
✓ मेटाडाटा प्रबंधन;
✓ विकास वातावरण;
✓ वर्कफ़्लो;
✓ सहयोग.
तीसरी श्रेणी के लिए क्षमताओं को शामिल किया गया:
✓ ऑनलाइन एनालिटिकल प्रोसेसिंग;
✓ विज़ुअलाइज़ेशन;
✓ ज्ञान और पूर्वानुमान की डिलिवरी;
✓ परिणाम के मानचित्र.
पांच साल बाद गार्टनर एक नया "जादू चक्र बीआई प्लेटफार्मों के लिए" प्रकाशित,
है कि अभी भी के लिए वर्तमान है 2012. इस दस्तावेज में बीआई प्लेटफॉर्म के रूप में देखी जा करने के लिए जारी
सॉफ्टवेयर प्लेटफार्मों, देने से क्षमताओं ऊपर वर्णित. लेकिन दो और अधिक सुविधाओं
"ज्ञान के वितरण" श्रेणी में जोड़ा गया है, यानी खोज-आधारित बीआई
तथा मोबाइल बीआई.
बीआई प्लेटफार्मों की बुनियादी क्षमताओं को व्यापक रूप से चर्चा की गई है और अध्ययन किया,
तो इस कारण के लिए वे इस पत्र में विस्तार से विचार नहीं किया जाएगा. अधिक ध्यान होगा
दो नए विशेषताओं के लिए भुगतान किया, गार्टनर द्वारा की पेशकश की.
पहला अवसर खोज-आधारित बीआई है. मूलतः यह एक का एक आवेदन पत्र है
संरचित और असंरचित डेटा स्रोतों और उनके प्रभाग में खोज सूचकांक (संगठन)
उपाय और आयामों की एक वर्गीकरण संरचना में, जो उपभोक्ताओं को आसानी से कर सकते हैं
नेविगेट करने और पता लगाने के, एक गूगल की तरह इंटरफ़ेस का उपयोग.
खोज इंजन और डेटा गोदामों के बीच मूल अंतर है कि खोज है
इंजन बहुत लचीला कर रहे हैं और प्रारूप और जानकारी के प्रकार के किसी भी प्रकार का समर्थन - हो
यह संरचित या असंरचित. इस प्रकार खोज इंजन तेजी से विकास हो रहा से निपटने कर सकते हैं
डेटा संरचनाएं. मौजूदा और नए डेटा का अनुक्रमण (अज्ञात अब तक) नहीं करता
अतिरिक्त डेटा मॉडलिंग की आवश्यकता होती है. परम्परागत डेटा भंडारण वास्तुकला सीमित है
उस फैसले को सुविधाजनक बनाने के लिए आवश्यक हैं असंरचित डेटा से निपटने के लिए क्षमताओं-
बनाने और खोज इंजन "इस खाई को भरने". तुलना में, डेटा गोदामों की आवश्यकता होती है
समय न केवल गोदाम मॉडल बनाने के लिए, लेकिन यह भी के लिए नए डेटा जोड़ने. एक और
खोज इंजन के सकारात्मक सुविधा सामग्री के माध्यम से "नेविगेशन" के अपने आसानी है. पर
नेविगेशन के प्रत्येक चरण, खोज इंजन को छानने के लिए विभिन्न अवसर प्रदान करते हैं
अनुक्रमित किया गया है डेटा की भीड़ में सामग्री के अनुसार परिणाम और
लगभग वास्तविक समय में विश्लेषण किया. संबंधात्मक डाटाबेस प्रबंधन सिस्टम (आरडीबीएमएस)
जब तक वे के बारे में अलग कुछ ज्ञान के अधिकारी डेटा विश्लेषण के लिए स्थान नहीं है
डेटा के प्रकार. अर्थात्, एक खोज इंजन आसानी से किसी भी घटना है कि एक पर हुआ अनुसरण कर सकते हैं
कुछ ही समय में कुछ पल, पारंपरिक RDBMS का उपयोग करते समय एक खोज किया जा सकता है
केवल सख्ती से परिभाषित डेटा के क्षेत्र में

QlikView संस्करण 13 रिलीज़ की तारीख

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, आदि.


Ease of Learning Qlikview Version 13

QlikView संस्करण 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. संक्षेप में, 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.


Predictive Analytics

Predictive Analytics will help your organisation reveal and predict trends, anticipate business change, and drive moire empirical strategic decision making with using a range of predictive analysis software.

Predictive analytics can be used to describe any approach to data mining with five attributes:

  1. Prediction (rather than description, classification or clustering),
  2. Agile and rapid analysis measured in hours or days
  3. Highly business relevant e.g. why did we sell x many widgets in New York (no complex ivory tower analyses)
  4. Easy to use
  5. Highly visual analytical results (no complex tables / जानकारी)


Predictive Analytics

In our experience the way to succeed with Predictive Analysis is to Empower a C-Level Predictive Analytics Champion. Recently we have worked with a large retail organisation with a CFO who was hugely keen on predictive analysis to help drive business growth and spot new market opportunities.


TIBCO Spotfire CostOptions and Pricing

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, Oracle, 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).

टीIBCO 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 version 6 Review

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.

During our 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 NetWeaver Business Warehouse 7.0.1
• Teradata Aster 5.0, 5.11
• Teradata 12.10, 13.00, 13.10, 14.00, 14.10

What is a Data Scientist?

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. However, 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.