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IBMSPSSMBPDM IBM SPSS Modeler - Business(R) Partner Data Mining Associate

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IBMSPSSMBPDM exam Dumps Source : IBM SPSS Modeler - Business(R) Partner Data Mining Associate

Test Code : IBMSPSSMBPDM
Test Name : IBM SPSS Modeler - Business(R) Partner Data Mining Associate
Vendor Name : IBM
Q&A : 25 Real Questions

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IBM IBM SPSS Modeler -

IBM Watson Studio: Product Overview and perception | killexams.com Real Questions and Pass4sure dumps

down load the authoritative ebook: Cloud Computing 2019: using the Cloud for competitive talents

See the full checklist of desktop studying SolutionsSee person reports of IBM Watson Studio

final analysis

Watson is an umbrella for all IBM deep studying and synthetic intelligence, in addition to computer discovering. The company became a pioneer in introducing AI technologies to the business world. What this capacity for buyers: Watson Studio is a suitable contender for any firm looking to set up machine studying and deep discovering applied sciences.

The platform offers wide equipment and technologies for information scientists, developers and area matter experts that desire to explore facts, build models, and instruct and install desktop discovering models at scale. The answer contains equipment to share visualizations and outcomes with others. Watson Studio helps cloud, laptop and native deployment frameworks.

The latter resides behind a company’s firewall or as a SaaS solution operating in an IBM private cloud. IBM Watson Studio is ranked as a “chief” in the Forrester Wave. It became a valued clientele’ option 2018 recipient at Gartner Peer Insights.

Product Description

Watson Studio relies on a collection of IBM tools and applied sciences to build potent computing device studying purposes and features. This contains IBM Cloud pretrained machine discovering models similar to visual recognition, Watson natural Language Classifier, and others. The ambiance makes use of Jupyter Notebooks along with different open supply tools and scripting languages to enhance constructed-in collaborative challenge features.

https://o1.qnsr.com/log/p.gif?;n=203;c=204660772;s=9478;x=7936;f=201812281334210;u=j;z=TIMESTAMP;a=20403954;e=i

The result is an atmosphere that allows fast and strong computing device studying construction and satisfactory tuning of fashions. facts scientists and others can choose from a number of capacities of Anaconda, Spark and GPU environments.

Watson Studio supports greater visual modeling via a drag-and-drop interface provided by using IBM’s SPSS Modeler. moreover, it contains automated deep researching the usage of a drag-and-drop, no-code interface in Neural network Modeler.

Overview and lines user Base

statistics scientists, developers and discipline rely specialists.

Interface

Graphical drag-and-drop and command line.

Scripting Languages/codecs Supported

supports Anaconda and Apache Spark. The latter offers Scala, Python and R interfaces.

formats Supported

Most major records and file formats are supported through open supply Jupyter Notebooks.

Integration

IBM Watson Studio connects several IBM products, including SPSS Modeler and statistics Science journey (DSX) together with open source equipment, with a view to deliver a sturdy Predictive Analytics and desktop studying (PAML) answer.

The ambiance accommodates open records units via Jupyter Notebooks, Apache Spark and the Python Pixiedust library. The cloud version aspects interactivity with pc servers and R Studio, together with Python, R., and Scala coder for records scientists.

Reporting and Visualization

Visualization through SPSS Modeler. mighty logging and reporting capabilities are built into the product.

Pricing

IBM has adopted a pay-as-you-go model. Watson Studio Cloud – normal charges $ninety nine monthly with 50 means unit hours per 30 days blanketed. Watson Studio Cloud - enterprise runs $6,000 per 30 days with 5,000 capability unit hours. Watson Studio computing device costs $199 per thirty days with unlimited modeling. Watson Studio local – for commercial enterprise records science groups N/A.

IBM Watson Studio Overview and features at a look:

seller and contours

IBM Watson Studio

ML center of attention

large statistics science center of attention with cloud and computer ML structures.

Key points and capabilities

powerful visual attention and natural classification equipment. bendy strategy that incorporates open source equipment. Connects to IBM SPSS Modeler.

user feedback

incredibly rated for features and capabilities. Some complaints revolving around using notebooks.

Pricing and licensing

Tiered model from $99 per thirty days per user to $6,000 per month per user or extra at business stage.


IBM Watson Studio is Coming to Your computing device | killexams.com Real Questions and Pass4sure dumps

example of a Modeler flow working on Watson Studio desktop

IBM Watson Studio is an incredibly powerful data science offering. in case you’re not widespread, Watson Studio is an integrated environment designed to make it easy to boost, coach, and control fashions. It comprises a big choice of equipment used for everything from statistics prep and mix to photograph attention. And now Watson Studio is on its method to your home windows or Mac laptop machine.

Overview of Watson Studio

Watson Studio contains a whole lot of equipment all inside one integrated atmosphere. the most familiar tools of Watson Studio are:

  • SPSS Modeler for data prep, blend, and modeling devoid of coding
  • data Refinery, a spreadsheet vogue tool, that allows for quickly, self-provider information guidance
  • Python, R, and Scala Jupyter Notebooks to create and share files that comprise live code, equations, visualizations, and explanatory textual content
  • Neural community Modeler for designing TensorFlow, Keras, PyTorch and Caffe structures devoid of coding
  • Interactive Dashboards to bring sharable are living studies so the conclusion clients can discover their own insights
  • accessible Deployment alternate options

    Watson Studio will soon be obtainable as three deployment alternatives:

  • Watson Studio on the IBM Cloud is the easiest way to get began. It presents 3 tiers from a free starter tier with pay-as-you-go compute all of the way to an business version.
  • Watson Studio local is our in the back of-the-firewall answer featuring a comfortable method to add Watson Studio capabilities to your commercial enterprise. includes buy options for a handful of users or the total corporation.
  • And coming soon: Watson Studio computer
  • Introducing Watson Studio desktop

    Watson Studio computer is our new 3rd deployment option in the Watson Studio household. It takes probably the most established parts of what's accessible inside Watson Studio on the cloud and ports it to your home windows or Mac computing device for offline use, for analysis of data data you don’t are looking to add, and for snappy efficiency. All with a fast and straightforward laptop setting up.

    Watson Studio on the desktop will scale from an individual consumer the entire way up to a big team, and will be a good addition to the Watson Studio household together with our cloud and local flavors.

    The initial main aspects of Watson Studio desktop can be a SPSS Modeler canvas together with the facts refinery spreadsheet editor. this may include backwards compatibility for SPSS Modeler streams.

    advantages of Watson Studio laptop
  • It’s speedy, notably for native files. boost particular person productivity using a locally put in client.
  • It offers offline use. are looking to construct a mannequin on a aircraft without WiFi? Watson Studio laptop will work devoid of an internet connection for weeks at a time.
  • Adhere to safety and governance mandates together with your records. Watson Studio computer permits your entire information to stay for your desktop.
  • unlimited modeling devoid of overages. the use of Watson Studio computer, which you could enhance models with none incremental cost. This permits you to construct fashions iteratively to your computing device, then circulation it to Watson Studio on the Cloud to installation.
  • It’s one Watson Studio, so no re-studying required. With the equal designs as the cloud and native versions, switching between deployment options is seamless without a pleasing working towards.
  • And identical to the relaxation of Watson Studio, any individual — coders or non-coders — may be able to prepare, blend, discover, and model their facts in barely minutes.
  • Watson Studio computer’s powerful graphing skillsJoin the Beta

    The Beta for Watson Studio is starting now with two equipment already ported to the desktop: a refreshed edition of SPSS Modeler & information Refinery. it'll additionally consist of initiatives to prepare your work, records property firm, and a convenient verify for updates feature.

    join the beta to provide comments on how you like these tools, and recommend which other tools we carry to the computer. The Beta is a part of the IBM SPSS Modeler Subscription Trial, so once you register for that you just’ll have access to each downloads.

    After you register, search for the “IBM SPSS Modeler Subscription Trial” card, click down load, you then’ll see the Watson Studio computer Beta downloads on the right hand facet of the web page.

    join the dialogue on the beta neighborhood

    After registering for the beta, join within the discussion on the Watson Studio desktop beta neighborhood. here you can ask questions in regards to the beta, deliver options for future features, get forum assist, and take part in beneficial surveys to influence product direction. be a part of the forum here with the aid of logging in with your IBMid.

    look ahead to future announcements here about this pleasing addition for the Watson Studio family.

    Watson Studio laptop venture organizer

    IBM, SAS, and SAP Listed as Visionary Leaders with the aid of 360Quadrants for Predictive Analytics | killexams.com Real Questions and Pass4sure dumps

    PUNE, India, Feb. 27, 2019 /PRNewswire/ -- 360Quadrants powered through MarketsandMarkets™, the world's handiest evaluation platform that combines skilled analysis with crowdsourced insights has released a quadrant on Predictive Analytics application to help businesses make sooner and greater informed decisions. the first unlock of the quadrant has IBM, SAS, and SAP sharing house as Visionary Leaders. 360Quadrants are generated submit analysis of businesses (product portfolios and business approach). Quadrants will be up to date each three months, and the place of providers will reflect how consumers, trade experts, and different providers expense them on diverse parameters.

    Quadrant highlights

    one hundred fifty+ groups offering predictive analytics utility were analyzed of which 31 organizations were shortlisted and labeled on a quadrant beneath Visionary Leaders, Innovators, Dynamic Differentiators, and rising Leaders.

    IBM SPSS Modeler, SAS advanced Analytics, SAP company Objects, FICO decision administration Suite, Tableau application, RapidMiner Studio, Oracle advanced Analytics, and Angoss expertise Studio were identified as visionary leaders as they have dependent product portfolios and a strong market presence and enterprise method.

    tips Builders WebFocus, Knime AG, MicroStrategy, NTT Analytics answer, Alteryx Predictive Analytics, Dataiku, GoodData, and TIBCO Spotfire were identified as innovators as they have got focused product portfolios, but a mediocre company method.

    AgileOne Cortex, Kognito, Exago, Qlik View, 6Sense ABM Orchestration Platform, figure Eight, Opera solutions signal Hub, Radius Intelligence, Domino data Lab, Civis Analytics, and Lytics have been recognized as emerging organizations as they've a niche product providing but poor business approach. Greenwave Axon Predict, Teradata Analytics, Microsoft Azure computing device getting to know, and Sisense were recognized as dynamic differentiators.

    The 360Quadrants platform provides the most granular predictive analytics utility evaluation between carriers.

    Methodology

    The methodology used to rank predictive analytics software corporations worried the use of extensive secondary research to determine key carriers by relating to annual experiences, press releases, investor shows, white papers, and quite a lot of connected directories and databases. 31 key companies had been shortlisted on the groundwork of their breadth of product choices, organization dimension, and different criteria. The rankings and weights for shortlisted companies in opposition t every parameter were finalized post analysis.  After the rankings have been finalized, each and every vendor became positioned in respective quadrants based on their score within the product offering and business strategy parameters.

    About 360Quadrants

    360Quadrants nearly compares companies in emerging applied sciences on 6 wide maturities: product maturity, enterprise maturity, use-case maturity, funding maturity, technology maturity, and business outcome maturity. each and every company is reviewed via 4 stakeholders—consumers, business consultants, other vendors, and MarketsandMarkets analysts—to make it unbiased. 360 aims to simplify and de-chance complicated buy decisions. patrons get to customise their quadrant in opposition t their particular needs. The mixed insights from peers, analysts, experts, and companies cut the bias and helps the buyer locate the ultimate healthy answer. vendors get to place themselves to win most excellent new purchasers, personalize their quadrants, come to a decision key parameters, and place themselves strategically in a spot area, to be consumed via giants and start-usaalike. experts get to grow their own manufacturer and raise their idea management. The 360 platform ambitions the constructing of a social community that links trade experts with businesses global.

    360Quadrants has also launched quadrants in fields like application Modernization features, AI in Fintech solutions, and Cognitive Analytics options.

    About MarketsandMarkets™

    MarketsandMarkets™ provides quantified B2B research on 30,000 high boom area of interest opportunities/threats which will influence the revenues of 70% to eighty% of corporations worldwide. MarketsandMarkets™ presently features 7500 shoppers international including eighty% of international Fortune 1000 companies. almost 75,000 exact officers across eight industries international approach MarketsandMarkets™ for their ache features around revenues choices.

    Contact:Mr. Manoj Singhvimanoj.singhvi@marketsandmarkets.comMarketsandMarkets™ research deepest Ltd.Tower B5, office 101, Magarpatta SEZ,Hadapsar, Pune - 411013, IndiaPhone: +1-888-600-6441

    View original content:http://www.prnewswire.com/information-releases/ibm-sas-and-sap-listed-as-visionary-leaders-by means of-360quadrants-for-predictive-analytics-300803125.html

    source MarketsandMarkets

    Copyright (C) 2019 PR Newswire. All rights reserved


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    IBM SPSS Modeler - Business(R) Partner Data Mining Associate

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    Your guide to the top big data certifications today | killexams.com real questions and Pass4sure dumps

    IDG

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    Data and big data analytics are fast becoming the lifeblood of any successful business. Getting the technology right can be challenging, but building the right team with the right skills to undertake big data initiatives can be even harder.

    Not surprisingly, that challenge is reflected in the rising demand for big data skills and certifications. According to research by IT research firm Foote Partners, both noncertified advanced data analytics skills and certified big data skills have gained value in recent years: with 74 advanced data analytics related skills and certifications rising in average value by 6 percent in 2015, followed by 116 advanced data analytics related skills and certifications increasing 4.8 percent overall in market value in 2016. Additionally, Foote Partners research found 123 related certified and noncertified big data skills seeing a 0.3 percent gain in value in the first quarter of 2017.

    Organizations are on the hunt for data scientists and analysts with expertise in the techniques required to analyze big data. They also need big data systems architects to translate requirements into systems, data engineers to build data pipelines, developers who know their way around Hadoop clusters and other technologies, and systems administrators and managers to tie everything together.

    [ Find out the hottest data and analytics trends today. | Get ahead with the top certs for big data, project management, agile, and the cloud. | Get weekly career tips by signing up for our CIO Leader newsletter. ]

    These skills are in high demand and are relatively rare. Individuals with the right mix of experience and skills can demand high salaries. The right certifications can help.

    "Advanced data analytics capabilities are just too critical for staying competitive," David Foote, co-founder, chief analyst and chief research officer of Foote Partners, said in a statement released with the research. "They've expanded in popularity from a few industries to nearly every industry and market. And there is the Internet of Things, the next critical focus for data and analytics services. IDC is predicting a 30 percent CAGR over the next five years, while McKinsey is expecting IoT to have a $4 trillion to $11 trillion global economic impact by 2025 as businesses look to IoT technologies to provide more insight."

    While the market value of noncertified advanced analytics skills has actually increased faster as a percentage of base salary than the value of certified big data skills, according to Foote Research, Foote believes pay premiums for both noncertified and certified skills will steadily rise over the next 12 to 24 months.

    If you're looking for a way to get an edge — whether you're job hunting, angling for a promotion or just want tangible, third-party proof of your skills — big data certification is a great option. Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. The number of big data certs is expanding rapidly.

    Below is our guide to the most sought after big data certifications to help you decide which cert is right for you.

    If you would like to submit a big data certification to this directory, please email us.

    Analytics: Optimizing Big Data Certificate

    The Analytics: Optimizing Big Data Certificate is an undergraduate-level program intended for business, marketing and operations managers, data analyst and professionals, financial industry professionals, and small business owners. The program brings together statistics, analysis, and written and oral communications skills. It introduces students to the tools needed to analyze large datasets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, building analytics models, finding the best model to explore correlation among variables and more.

    Organization: University of Delaware

    Price: $2,895 course fee

    How to prepare: A basic background in statistics and some prior college coursework is recommended.

    Certificate in Engineering Excellence Big Data Analytics and Optimization (CPEE)

    Offered in Hyderabad and Bengaluru, India, the Certificate in Engineering Excellence Big Data Analytics and Optimization is an intensive 18-week program that consists of 10 courses (lectures and labs) for students of all aspects of analytics, including working with big data using Hadoop. It focuses on R and Hadoop skills, as well as statistical modeling, data analytics, machine learning, text mining and optimization. Students are evaluated on a real-world capstone project and a series of quizzes.

    Organization: International School of Engineering (INSOFE)

    Price: ₹3000 (INR) application fee and a program fee of ₹3,25,000 + 15 percent service tax.

    How to prepare: INSOFE admits students based on performance on its entrance exam and prior academic background and work experience.

    Certification of Professional Achievement in Data Sciences

    The Certification of Professional Achievement in Data Sciences is a non-degree program intended to develop facility with foundational data science skills. The program consists of four courses: Algorithms for Data Science (CS/IEOR), Probability & Statistics (STATS), Machine Learning for Data Science (CS), and Exploratory Data Analysis and Visualization (STATS).

    Organization: Columbia University

    Price: $1,858 per credit (a minimum of 12 credits, including the four courses, are required to complete the program). In addition, there is an $85 non-refundable application fee for the on-campus program and $150 for the online program. The online program also includes an additional non-refundable technology fee of $395 per course.

    How to prepare: An undergraduate degree and prior quantitative and introductory to computer programming coursework are required.

    Certified Analytics Professional

    The Certified Analytics Professional (CAP) credential is a general analytics certification that certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment and model lifecycle management. It requires completion of the CAP exam and adherence to the CAP Code of Ethics.

    Organization: INFORMS

    Price: $495 if you are an INFORMS member, or $695 if you're not. Team pricing is available for organizations. 

    How to prepare: A list of study courses and a series of webinars are available through registration.

    Cloudera Certified Associate (CCA) Data Analyst

    A SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform and model Hadoop data to define relationships and extract meaningful results from the raw output. It requires passing the CCA Data Analyst Exam (CCA159), a remote-proctored set of eight to 12 performance-based, hands-on tasks on a CDH 5 cluster. Candidates have 120 minutes to implement a technical solution for each task. They must analyze the problem and arrive at an optimal approach in the time allowed.

    Organization: Cloudera

    Price: $295

    How to prepare: Cloudera recommends candidates take the Cloudera Data Analyst Training course, which has the same objectives as the exam.

    Cloudera Certified Associate (CCA) Spark and Hadoop Developer

    The CCA Spark and Hadoop Developer credential certifies a professional has proven their core skills to ingest, transform and process data using Apache Spark and core Cloudera enterprise tools. It requires passing the remote-proctored CCA Spark and Hadoop Developer Exam (CCA175), which consists of eight to 12 performance-based, hands-on tasks on a Cloudera Enterprise cluster. Each question requires the candidate to solve a particular scenario. Some cases may require a tool such as Impala or Hive, others may require coding. Candidates have 120 minutes to complete the exam.

    Organization: Cloudera

    Price: $295

    How to prepare: There are no prerequisites required, but Cloudera says the exam follows the same objectives as the Cloudera Developer Training for Spark and Hadoop course, making it excellent preparation for the exam.

    Cloudera Certified Professional (CCP): Data Engineer

    The CCP: Data Engineer credential certifies the ability to perform core competencies required to ingest, transform, store and analyze data in Cloudera's CDH environment. It requires passing the remote-proctored CCP: Data Engineer Exam (DE575), a hands-on, practical exam in which each user is given five to eight customer problems each with a unique, large data set, a CDH cluster and four hours. For each problem, the candidate must implement a technical solution with a high degree of precision that meets all the requirements.

    Organization: Cloudera

    Price: $400

    How to prepare: Cloudera suggests professionals seeking this certification have hands-on experience in the field and take the Cloudera Developer Training for Spark and Hadoop course.

    EMC Proven Professional Data Scientist Associate (EMCDSA)

    The EMCDSA certification demonstrates an individual's ability to participate and contribute as a data science team member on big data projects. It includes deploying the data analytics lifecycle, reframing a business challenge as an analytics challenge, applying analytic techniques and tools to analyze big data and create statistical models, selecting the appropriate data visualizations and more.

    Organization: Dell EMC Education Services

    Price: $600 for video-ILT streaming; $5,000 for instructor-led

    How to prepare: EMC offers a training course, available as either a video or an instructor-led course.

    IBM Certified Data Architect – Big Data

    Designed for data architects, the IBM Certified Data Architect – Big Data certification requires passing a test that consists of five sections containing a total of 55 multiple-choice questions. It demonstrates a data architect can work closely with customers and solutions architects to translate customers' business requirements into a big data solution.

    Organization: IBM Professional Certification Program

    Price: $200

    How to prepare: IBM recommends a series of seven multi-day courses on SPSS Modeler to InfoSphere BigInsights to prepare for the test.

    IBM Certified Data Engineer – Big Data

    The IBM Certified Data Engineer – Big Data certification is intended for big data engineers, who work directly with data architects and hands-on developers to convert an architect's big data vision into reality. Data engineers understand how to apply technologies to solve big data problems and have the ability to build large-scale data processing systems for the enterprise. They develop, maintain, test and evaluate big data solutions within organizations, providing architects with input on needed hardware and software. This certification requires passing a test that consists of five sections containing a total of 53 multiple-choice questions.

    Organization: IBM Professional Certification Program

    Price: $200

    How to prepare: IBM recommends a series of nine multi-day courses to prepare for the test.

    Mining Massive Data Sets Graduate Certificate

    Designed for software engineers, statisticians, predictive modelers, market researchers, analytics professionals, and data miners, the Mining Massive Data Sets Graduate Certificate requires four courses and demonstrates mastery of efficient, powerful techniques and algorithms for extracting information from large datasets like the Web, social network graphs and large document repositories. The certificate usually takes one to two years to complete.

    Organization: Stanford Center for Professional Development

    Price: $18,000 tuition

    How to prepare: A Bachelor's degree with an undergraduate GPA of 3.0 or better is required. Applicants should have knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program.

    MongoDB Certified DBA Associate

    The MongoDB Certified DBA Associate credential is intended to demonstrate that operations professionals understand the concepts and mechanics required to administrate MongoDB. It requires a 90 minute, multiple choice exam.

    Organization: MongoDB University

    Price: $150

    How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M102: MongoDB for DBAs; M202: MongoDB Advanced Deployment Operations). MongoDB also provides the MongoDB Certification Exam Study Guide, available to those who have registered for a certification exam.

    MongoDB Certified Developer Associate

    The MongoDB Certified Developer Associate credential is intended for software engineers who want to demonstrate a solid understanding of the fundamentals of designing and building applications using MongoDB. It requires a 90 minute, multiple choice exam.

    Organization: MongoDB University

    Price: $150

    How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M101J: MongoDB for Java Developers; M101JS: MongoDB for Node.js Developers; M101N: MongoDB for .NET Developers; M101P: MongoDB for Developers). MongoDB also provides the MongoDB Certification Exam Study Guide, available to those who have registered for a certification exam.

    SAS Certified Big Data Professional

    The SAS Certified Big Data Professional certification program is for individuals seeking to build on their basic programming knowledge by learning how to gather and analyze big data in SAS. The program focuses on SAS programming skills; accessing, transforming and manipulating data; improving data quality for reporting and analytics; fundamentals of statistics and analytics; working with Hadoop, Hive, Pig and SAS; and exploring and visualizing data. The program includes two certification exams, both of which the participants must pass.

    Organization: SAS Academy for Data Science

    Price: $9,000 for classroom (Cary, NC), $4,725 for blended learning (combination of 24/7 online access and instructor-led training)

    How to prepare: At least six months of programming experience in SAS or another programming language is required to enroll.

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    Gartner's Look at Advanced Analytics Vendors: Are You Using a Winner? | killexams.com real questions and Pass4sure dumps

    Gartners Look at Advanced Analytics Vendors Are You Using a Winner

    Hats off to Gartner for resisting the temptation to call Advanced Analytics “Analytics 3.0” because no one knows what that means. Some say that 3.0 suggests “analytics for all," referencing “all” as average workers.

    Advanced Analytics, by Gartner's definition, are anything but that, according to the Magic Quadrant for Advanced Analytics Platforms (registration required).

    Instead, Gartner defines them as “the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover."

    In other words, advanced analytics are the scalpels used by highly trained data scientists.

    2015-4-March-MQ-Advanced-Analytics Extracting Value

    This year’s Magic Quadrant for Advanced Analytics report acknowledges that the tools are becoming friendlier to business analysts and citizen data scientists. But based on the reporting we’ve done around the various vendors in the past 16 months, we’re not holding our breath.

    Data workers using great, clean data sets and the right tools extract value.

    That being said, here are the vendors Gartner selected as leaders for its MQ for Advanced Analytics Platforms.

    Still SAS-sy

    SAS’s analytics software has been around since 1976, yet no one is ready to call it a relic. In fact, with 40,000 customers and the largest ecosystem of users and partners, it’s the clear leader in this year’s MQ with only IBM ranking anywhere near it.

    What’s so special? Aside from its completeness of vision and ability to execute, Gartner claims it has the widest product stack in the industry. Not only that, but its community is strong and users praise its training as well as the performance, scalability, stability and reliability of the platform.

    On the downside Gartner notes that SAS offers multiple products with similar capabilities (for example, predictive modeling) and that this can cause confusion. Ditto for interoperability and consistent UIs between them.

    And though third generation advanced analytics vendors argue that they offer a different and more modern approach (browser vs. client server, big data and Hadoop versus data warehouses) Gartner indicates price is the primary reason companies look for SAS alternatives.

    We should note that SAS is getting friendly with open source via integrations and initiatives such as ODP.

    IBM Analytics Before and After Watson

    With all the press we see about IBM’s consistently poor quarterly results, it is easy to forget that it is a leader and a groundbreaker on other fronts. Analytics is one of them

    Gartner says one of the strengths of IBM’s SPSS Modeler products and solutions is that they apply to a gamut of analytic challenges relating to customers, operations, physical assets and risks.

    It would be interesting to see how they relate to Watson’s new industry offerings. Gartner says that it might behoove IBM to clarify this for us all.

    That being said, IBM’s community of experienced employees and users rate its products highly, especially when you look at them one at a time. The challenge for any vendor that has been in a market for many years is keeping it simple and experiences consistent.

    On the downside, IBM seems weak on the non-geeky stuff like account management, training, technical support and that user feedback isn’t necessarily taken account on product road maps.

    KNIME Proves Open Source Is Viable

    Is Open Source the way to go with big data and analytics? Maybe not so much. Or at least not yet. That being said, KNIME breaks that rule, and quite impressively. Gartner likes its openness, which allows companies to build their own customized features and to work with the tools of their choosing, like R and Python. Not only that, but any open source project that succeeds owes it largely to an enthusiastic community that KNIME has.

    Still, Gartner has some concerns, many KNIME enthusiasts are data miners. So it would be good to broaden the platform's appeal. Not only that, but the UI and visualizations could also be more attractive.

    RapidMiner Moves Toward the Cloud, Big Data

    RapidMiner is open source, client-server based solution but it will cost you to take it to the cloud. Still, it could be worth your dollars and cents. Gartner likes the ground that RapidMiner covers both in terms of breadth and depth. Ditto for its innovation as it moved toward big data, cloud and industry accelerators.

    On the downside the user base is mostly data scientists. In addition, a whole gamut of customer oriented services are on the slide. That being said, there’s a new leadership team in house and (this is our two cents). Maybe it’ll focus on fixing the shortcomings.

    Visionaries: They Could Be Leaders

    Alteryx, Alpine Data and Microsoft are all speeding toward Gartner’s leaders’ quadrant, in many cases offering something that the leaders don’t or at least not via as delightful a user experience.

    Alteryx Is Just a Hair Away

    The promise of the big data age is to generate better insights using significantly more data. But blending data sources is difficult unless you use Alteryx, that is. At least that’s the company’s promise.

    If it’s true that organizations that leverage data best will win the future then Alteryx or a tool like it could be key. It helps users integrate internal data, third party data and cloud data without any coding. Drag and drop replaces R, which, through almost anyone’s eyes, is a beautiful thing.

    Gartner likes Alteryx’s new sales strategy, which encourages customers to first go after small wins, the idea being that based on that, it can later expand its footprint. It also noted its integrations with Revolution Analytics and Apache Spark as big plusses.

    On the downside its visualization capabilities which are commonly expressed via Tableau are sometimes criticized by customers—they want Alteryx to offer their own (they do offer some, but they don’t yet compare to Tableau’s. And though its documentation is weak, customer service is strong, according to Gartner.

    Our experience interacting with Alteryx executives is that they’re confident in the value their product provides, determined to meet customer needs, and delight. There’s only a fine line between their positions in the visionaries quadrant and where the leaders reside. We expect to see them there next year.

    Alpine's Vision for the Big Data Era

    Alpine Data Labs built its analytics solutions for the age of big data and the third platform. Their solution is browser based and it analyzes big datasets by running analytic workflows natively within existing Hadoop or other parallel platforms. Alpine’s Chorus tool makes it easy for business users and data analysts to collaborate while creating models.

    Gartner likes Alpine’s commitment toward cloud based analysis which shortens time to value (and results). Its scalability and attention to customer feedback rates highly.

    And while some are concerned by Alpine’s size and market share, it’s worth noting that yesterday the company announced that they have ten times as many users as they had in 2013. So this could be a short-lived problem.

    “Sure we’re not as big as SAS, but we’re not 30 years old either,” Bruno Aziza, Alpine Data Labs’ CMO told me in a recent conversation. And there’s a benefit to that, they can spend their energies building what’s new, and ground breaking — it’s harder for older companies to do that because they have existing products to maintain and protect.

    Not only that, but “no one else can do what we can do,” Aziza pointed out, explaining that Alpine is one of the few (or maybe the only) Gartner rated Advanced Analytics vendor that leverages all brands of Hadoop, Apache Spark, and other data sources.

    Microsoft Capitalizes on Reach, Machine Learning

    Microsoft’s broad enterprise reach via Windows, Office, SharePoint, SQL Server and Exchange product lines provide it inherent advantages. Though its predictive analytics capability (SQL Server Analysis Services [SSAS]) embedded within SQL Server may be a bit stiff and tired, its new Azure Machine Learning (AML) capabilities are as cool as anything you can find at a smart, ambitious startup. If it wasn’t for them, Microsoft may have missed a spot in the Visionaries MQ.

    Gartner says that Microsoft's AML is impressive in that it brings together best of breed components (extraction, transformation and loading [ETL], data storage, data preparation, different analytics and presentation layers) and integration with T and R packages. AML is a radically different product than SSAS and will likely overtake it before long.

    Microsoft can also leverage its cloud to provide PaaS, which give it clear advantages.

    If you’re an Enterprise in search of Advanced Analytics solutions, these are good times. There are many, well-differentiated, great choices.



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