SPS-202 exam Dumps Source : IBMSPSSMBPDM- IBM SPSS Modeler Business(R) partner Data Mining Associate
Test Code : SPS-202
Test title : IBMSPSSMBPDM- IBM SPSS Modeler Business(R) partner Data Mining Associate
Vendor title : IBM
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down load the authoritative e-book: Cloud Computing 2019: the usage of the Cloud for aggressive advantage
See the all checklist of computing device gaining learning of SolutionsSee consumer experiences of IBM Watson Studiobottom line
Watson is an umbrella for outright IBM abysmal discovering and synthetic intelligence, in addition to laptop learning. The company became a pioneer in introducing AI technologies to the traffic world. What this potential for patrons: Watson Studio is a exact contender for any company looking to deploy laptop studying and abysmal researching applied sciences.
The platform gives extensive paraphernalia and technologies for facts scientists, builders and field depend consultants that necessity to determine information, build models, and educate and set up computer gaining learning of fashions at scale. The retort contains paraphernalia to partake visualizations and results with others. Watson Studio helps cloud, computer and local deployment frameworks.
The latter resides behind a firm’s firewall or as a SaaS solution working in an IBM deepest cloud. IBM Watson Studio is ranked as a “chief” within the Forrester Wave. It turned into a customers’ option 2018 recipient at Gartner Peer Insights.Product Description
Watson Studio relies on a group of IBM tools and applied sciences to construct efficient computing device getting to know purposes and services. This comprises IBM Cloud pretrained computing device studying fashions corresponding to visible recognition, Watson herbal Language Classifier, and others. The environment makes consume of Jupyter Notebooks together with other open supply tools and scripting languages to complement constructed-in collaborative undertaking points.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 outcome is an ambiance that enables quick and powerful laptop gaining learning of pile and quality tuning of models. facts scientists and others can create a election from a number of capacities of Anaconda, Spark and GPU environments.
Watson Studio supports better visual modeling through a drag-and-drop interface supplied by using IBM’s SPSS Modeler. furthermore, it accommodates automatic abysmal researching the consume of a drag-and-drop, no-code interface in Neural community Modeler.Overview and lines consumer Base
statistics scientists, builders and belt recall consultants.Interface
Graphical drag-and-drop and command line.Scripting Languages/formats Supported
supports Anaconda and Apache Spark. The latter offers Scala, Python and R interfaces.codecs Supported
Most major information and file codecs are supported through open supply Jupyter Notebooks.Integration
IBM Watson Studio connects a yoke of IBM items, together with SPSS Modeler and records Science event (DSX) together with open supply tools, with a view to bring a tenacious Predictive Analytics and laptop getting to know (PAML) solution.
The ambiance accommodates open data sets through Jupyter Notebooks, Apache Spark and the Python Pixiedust library. The cloud edition features interactivity with computer servers and R Studio, together with Python, R., and Scala coder for facts scientists.Reporting and Visualization
Visualization via SPSS Modeler. tenacious logging and reporting capabilities are developed into the product.Pricing
IBM has adopted a pay-as-you-go model. Watson Studio Cloud – mediocre expenses $ninety nine per month with 50 means unit hours per month covered. Watson Studio Cloud - traffic runs $6,000 per month with 5,000 capability unit hours. Watson Studio laptop charges $199 per thirty days with limitless modeling. Watson Studio local – for enterprise records science teams N/A.IBM Watson Studio Overview and contours at a look:
seller and contours
IBM Watson Studio
wide information science center of attention with cloud and desktop ML structures.
Key features and capabilities
powerful visible awareness and herbal classification equipment. resilient strategy that accommodates open source tools. Connects to IBM SPSS Modeler.
particularly rated for points and capabilities. Some complaints revolving round using notebooks.
Pricing and licensing
Tiered mannequin from $99 per month per user to $6,000 per 30 days per consumer or more at enterprise level.
Two of IBM’s most established evaluation products, the Cognos company Intelligence and the SPSS predictive analytics equipment, are headed for the cloud, the newest in an ongoing push by using IBM to port its substantial utility portfolio to the cloud.
having access to this sort of application from a hosted atmosphere, in location of procuring the paraphernalia outright, offers a number of advantages to purchasers.
“We manage the infrastructure, and this permits you to scale more effortlessly and congregate outright started with less upfront investment,” pointed out Eric Sall, IBM vice president of global analytics marketing.
IBM introduced these additions to its cloud functions, as well as a few current choices, at its perception user conference for records analytics, held this week in Las Vegas.
by 2016, 25 p.c of recent enterprise analysis deployments can exist accomplished within the cloud, in keeping with Gartner.
Analytics might champion groups in lots of techniques, in line with IBM. It may supply further insight in the procuring habits of consumers, as well as insight into how neatly its personal operations are performing. It could help safeguard systems from assaults and attempts at fraud, as well as guarantee that traffic departments are assembly compliance requirements.
the current online edition of Cognos, IBM Cognos enterprise Intelligence on Cloud, can at the second exist validated in a preview mode. IBM plans to present Cognos as a replete traffic provider early next year. clients can quicken Cognos towards statistics they retain in the IBM cloud, or towards records they deliver on premises.
A replete traffic edition of the online IBM SPSS Modeler will exist purchasable within 30 days. This paraphernalia will encompass outright the SPSS add-ons for records based predictive modeling, akin to a modeler server, analytics conclusion administration software and a information server.
past this year, IBM pledged to proffer a all lot of its software portfolio as cloud services, many via its Bluemix set of platform functions.
besides Cognos and SPSS, IBM likewise unveiled a number of current and up-to-date offerings at the conference.
One current carrier, DataWorks, gives a yoke of options for refining and cleaning facts so it's equipped for evaluation. The company has launched a cloud-based data warehousing carrier, called dashDB. a brand current Watson-primarily based provider, called Watson Explorer, offers a way for users to request natural language questions on diverse units of interior information.To paw upon this text and other PCWorld content material, visit their fb page or their Twitter feed.
IBM Watson Studio is an exceedingly efficient information science offering. if you’re now not typical, Watson Studio is an built-in environment designed to create it smooth to increase, educate, and exploit models. It comprises a big election of paraphernalia used for every slight thing from records prep and mingle to picture consciousness. And now Watson Studio is on its solution to your windows or Mac desktop computer.Overview of Watson Studio
Watson Studio contains lots of tools outright inside one built-in atmosphere. the most regularly occurring paraphernalia of Watson Studio are:
Watson Studio will quickly exist purchasable as three deployment options:
Watson Studio desktop is their current third deployment option inside the Watson Studio family. It takes essentially the most frequent parts of what's available inside Watson Studio on the cloud and ports it to your windows or Mac computing device for offline use, for evaluation of information data you don’t are looking to upload, and for snappy performance. outright with a posthaste and simple desktop installing.
Watson Studio on the computer will scale from someone user outright of the way as much as a sizable team, and will exist a fine addition to the Watson Studio family together with their cloud and autochthonous flavors.
The initial leading features of Watson Studio computing device can exist a SPSS Modeler canvas in conjunction with the statistics refinery spreadsheet editor. this will encompass backwards compatibility for SPSS Modeler streams.merits of Watson Studio laptop
The Beta for Watson Studio is beginning now with two paraphernalia already ported to the computing device: a refreshed edition of SPSS Modeler & facts Refinery. it'll likewise consist of tasks to prepare your work, statistics assets organization, and a effortless check for updates function.
be piece of the beta to supply comments on the way you fancy these tools, and advocate which other tools they carry to the computer. The Beta is piece of the IBM SPSS Modeler Subscription Trial, so when you register for that you just’ll gain access to both downloads.
After you register, search for the “IBM SPSS Modeler Subscription Trial” card, click on down load, then you definately’ll contemplate the Watson Studio laptop Beta downloads on the preempt hand facet of the page.join the discussion on the beta neighborhood
After registering for the beta, exist a piece of within the discussion on the Watson Studio computing device beta neighborhood. here that you would exist able to request questions concerning the beta, supply strategies for future aspects, congregate forum assist, and recall piece in valuable surveys to gain an repercussion on product direction. exist a piece of the discussion board birthright here by means of logging in with your IBMid.
wait for future announcements birthright here about this pleasing addition for the Watson Studio household.Watson Studio computer task organizer
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Data and sizable data analytics are posthaste becoming the lifeblood of any successful business. Getting the technology birthright can exist challenging, but pile the birthright team with the birthright skills to undertake sizable data initiatives can exist even harder.
Not surprisingly, that challenge is reflected in the rising demand for sizable data skills and certifications. According to research by IT research arduous Foote Partners, both noncertified advanced data analytics skills and certified sizable data skills gain gained value in recent years: with 74 advanced data analytics related skills and certifications rising in mediocre 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 create 123 related certified and noncertified sizable 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 sizable data. They likewise necessity sizable 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. | congregate ahead with the top certs for sizable data, project management, agile, and the cloud. | congregate weekly career tips by signing up for their CIO Leader newsletter. ]
These skills are in lofty demand and are relatively rare. Individuals with the birthright mingle of sustain and skills can demand lofty salaries. The birthright 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 gain a $4 trillion to $11 trillion global economic repercussion by 2025 as businesses survey to IoT technologies to provide more insight."
While the market value of noncertified advanced analytics skills has actually increased faster as a percentage of ground salary than the value of certified sizable data skills, according to Foote Research, Foote believes pay premiums for both noncertified and certified skills will steadily ascend over the next 12 to 24 months.
If you're looking for a way to congregate an edge — whether you're job hunting, angling for a promotion or just want tangible, third-party proof of your skills — sizable data certification is a remarkable option. Certifications measure your learning and skills against industry- and vendor-specific benchmarks to prove to employers that you gain the birthright skillset. The number of sizable data certs is expanding rapidly.
Below is their usher to the most sought after sizable data certifications to help you resolve which cert is birthright for you.
If you would fancy to submit a sizable data certification to this directory, gladden email us.Analytics: Optimizing sizable Data Certificate
The Analytics: Optimizing sizable Data Certificate is an undergraduate-level program intended for business, marketing and operations managers, data analyst and professionals, fiscal industry professionals, and petite traffic owners. The program brings together statistics, analysis, and written and oral communications skills. It introduces students to the tools needed to analyze big datasets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, pile 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 sizable Data Analytics and Optimization (CPEE)
Offered in Hyderabad and Bengaluru, India, the Certificate in Engineering Excellence sizable Data Analytics and Optimization is an intensive 18-week program that consists of 10 courses (lectures and labs) for students of outright aspects of analytics, including working with sizable 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 sequence 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 likewise 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 generic analytics certification that certifies end-to-end understanding of the analytics process, from framing traffic 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.
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 sequence 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 gain 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.
How to prepare: Cloudera recommends candidates recall the Cloudera Data Analyst Training course, which has the selfsame 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 unravel a particular scenario. Some cases may require a tool such as Impala or Hive, others may require coding. Candidates gain 120 minutes to complete the exam.
How to prepare: There are no prerequisites required, but Cloudera says the exam follows the selfsame 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 faculty to achieve 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, big data set, a CDH cluster and four hours. For each problem, the candidate must implement a technical solution with a lofty degree of precision that meets outright the requirements.
How to prepare: Cloudera suggests professionals seeking this certification gain hands-on sustain in the field and recall the Cloudera Developer Training for Spark and Hadoop course.EMC Proven Professional Data Scientist Associate (EMCDSA)
The EMCDSA certification demonstrates an individual's faculty to participate and contribute as a data science team member on sizable data projects. It includes deploying the data analytics lifecycle, reframing a traffic challenge as an analytics challenge, applying analytic techniques and tools to analyze sizable data and create statistical models, selecting the preempt 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 – sizable Data
Designed for data architects, the IBM Certified Data Architect – sizable 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' traffic requirements into a sizable data solution.
Organization: IBM Professional Certification Program
How to prepare: IBM recommends a sequence of seven multi-day courses on SPSS Modeler to InfoSphere BigInsights to prepare for the test.IBM Certified Data Engineer – sizable Data
The IBM Certified Data Engineer – sizable Data certification is intended for sizable data engineers, who work directly with data architects and hands-on developers to transmogrify an architect's sizable data vision into reality. Data engineers understand how to apply technologies to unravel sizable data problems and gain the faculty to build large-scale data processing systems for the enterprise. They develop, maintain, test and evaluate sizable 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
How to prepare: IBM recommends a sequence 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 big datasets fancy the Web, gregarious network graphs and big 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 gain learning of basic computer science principles and skills, at a flat enough 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 election exam.
Organization: MongoDB University
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 likewise provides the MongoDB Certification Exam Study Guide, available to those who gain 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 pile applications using MongoDB. It requires a 90 minute, multiple election exam.
Organization: MongoDB University
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 likewise provides the MongoDB Certification Exam Study Guide, available to those who gain registered for a certification exam.SAS Certified sizable Data Professional
The SAS Certified sizable Data Professional certification program is for individuals seeking to build on their basic programming learning by learning how to congregate and analyze sizable 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 sustain in SAS or another programming language is required to enroll.Related articles Join the newsletter!
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You’re reading this article because you’re actively interested in text analytics technology and market trends. Whether you’re a solutions provider or consumer, you want to exist sure you’ve invested your time and fiscal resources wisely.
The picture is complex, however, as the text analytics domain is not dominated by any one algorithm or approach, vendor or traffic sector. So far, the diversity of options has benefitted potential users; awareness (and realization) of the technology’s capabilities is pile rapidly in areas such as media monitoring, publishing, customer-experience management and semantic search. Meanwhile, growth remains tenacious in domains that gain long applied text analytics. These areas include life sciences, intelligence and law enforcement, and fiscal services. While the text analytics domain isn’t unaffected by current traffic conditions, economic pressures could actually spur uptake motivated by a quest for efficiency through automation.Sources and Perspectives
To abide on top of trends, I try to talk to current and prospective users as often as I can, and I likewise try to withhold up with researchers and fellow analysts. (You’ll find links for some of the folks I succeed at my BeyeNETWORK channel.) I likewise catch up with vendors periodically.
Because it’s helpful to understand current industry perspectives, I recently invited CEOs, CTOs and thought leaders to respond to the following query:
What attain you contemplate as the 3 (or fewer) most essential text analytics technology, solution or market challenges in 2009?
Before relaying answers I received, I’ll mention two meta-replies. First, Marti Hearst, associate professor in the UC Berkeley School of Information, declined to respond, in piece because “…for me, 2009 is too immediate a time horizon.” This thought applies not only to academic researchers but likewise to anyone who’s thinking strategically, beyond this year’s crop of product releases and traffic conditions. Next, Lexalytics CEO Jeff Catlin candidly characterized his response as “somewhat self-serving thoughts.” No doubt many of the vendors quoted contemplate the greatest challenges as residing in areas their tools address, so recall their views with a grain of salt.
I’ll relay outright views with minimal editing, complete with vendor self-promotion because, after all, commercial products are “where the rubber hits the road” for most enterprise users.Text Analytics in 2009
Let’s start with Maria Milosavljevic, CTO at Capital Markets Cooperative Research Centre, an Australian group that is conducting leading-edge R&D in real-time security-market surveillance. The top 3 for Maria are:
Breck Baldwin of Alias-i, author of LingPipe natural language processing software, is very to-the-point in his reply, with a sort of twist on Maria’s expectations response.
#1 thing the field needs is a profound and existent success legend of text analytics.
The reply from Sid Banerjee, CEO of Clarabridge, looks at factors related to scaling text analytics to the enterprise, “the expansion of text analytics across a few dimensions.” His reply:
Aaron B. Brown of IBM similarly looks at architectural issues and likewise at traffic concerns. Aaron is Program Director, ECM Discovery, for IBM Information Management Software and has remarkable market and technical insights. I interviewed him final year on “Text Analytics for Legal Compliance.” That exchange is soundless a trustworthy read. Here are his thoughts on challenges for 2009:
Other replies likewise looked at traffic conditions and at experiences in the adoption and consume of text technologies. Lexalytics CEO Jeff Catlin foresees:
Craig Norris, CEO at Attensity, similarly famous three varieties of challenge, in his case relating to technology, implementation and seeing chance in adverse traffic conditions:
Vendor prognosticators with a solutions focus include Keith Collins, CTO at SAS, and Manya Mayes, SAS Chief Text Mining Strategist, contemplate as challenges for 2009:
Yves Schabes, President of Teragram, a SAS company, focuses his response on one particular challenge – increasing workers’ efficiency:
Given the current economic situation, big organizations are forced to withhold up a posthaste pace of traffic with fewer resources, and it is therefore critical that these organizations gain outright of their content organized correctly so that employees can expend more time fulfilling their jobs and less time searching for information on their enterprise's system.
Neil Hartley, CEO of Leximancer, sees “an industry that has been around for a long time and yet has seen slight in the way of being operationalized within traffic processes.” Neil continues:
Yes, there are proofs of concept, quicken by experienced vendor staff but these [prototypes], in my experience, rarely congregate adopted by the traffic a) because of the setup and maintenance required, and b) because the source data vocabulary changes making the initial setup redundant. Autonomy is the exception, but their deployments are largely search/retrieval-based and less qualitative.
What the traffic needs is a lofty degree of automation (without the necessity for inordinate setup and maintenance) together with clarity in the analysis and the faculty to apply control to the process where needed. This is exactly what Leximancer provides.
The other major trend I contemplate is the necessity to create gregarious media actionable, and this is something we’ve focused on heavily on their blog. I respect customer attitudes on gregarious media or microblogging sites are a leading indicator for the business. The traffic that waits for these trends to exist reflected in their formal feedback programs may find it is too late to recall efficient action.Technology and Applications
I had expected that a higher harmony of 2009 “challenges” responses would center on the technology and its applications. Responses I’ve already quoted paw on those areas with perhaps greater attention to traffic and market concerns. Eric Martin, Product Marketing Manager at SPSS, focused solely on solutions, which to me reflects both Eric’s self-confidence in his company’s market position and his own background: Eric earned a Ph.D. in immunology and cellular biology and, fancy many others, started using text mining on biomedical articles before joining text analytics pioneer LexiQuest, which was later acquired by SPSS. Challenge areas Eric sees for 2009 are:
Matthew Hurst of Microsoft Live Labs is likewise a techie at heart, and he’s likewise very interested in user-generated and other online content. Matthew says, “As reported elsewhere in research and industry literature, the majority of textual data being published online today is from the many genres of gregarious media. To fully leverage this data, the key challenges are:
Lastly, Ren Mohan, Co-Chairman and CTO of IxReveal, replied not only with the three challenges his company hears most often from their clients, but likewise with a yoke of “megatrends” he is beginning to see. Challenges are:
Ren’s “megatrends” are:
Ren’s conclusion: “These are truly exciting times!” Indeed.A Live Challenge?
Here are thoughts on one more potential challenge for 2009, a live challenge, of a different variety.
As an aside while forwarding his recall on 2009 text-analytics challenges, Lexalytics’ Jeff Catlin suggested a bake-off to exist held at the 2009 Text Analytics Summit, which is slated for June 1-2 (preceded by tutorials) in Boston. Jeff says in his blog, “Our market is soundless dominated by too much flashy marketing and not enough down in the dirt numbers for ‘apples to apples’ comparisons.” Jeff is right, although I’ll add that I believe that most of the flashy marketing actually fronts very capable products. Perhaps they can congregate something going for this year – a commercially oriented version of the TREC (Text REtrieval Conference) challenge. abide tuned, and attain respect attending this year’s summit.
And if you’re a current or prospective text analytics user and would fancy to command me about challenges you mug or hope to face, gladden attain congregate in paw by email at firstname.lastname@example.org or by phone at (301) 270-0795).
SOURCE: Perspectives on Text Analytics in 2009
Seth is a traffic intelligence and conclusion systems expert. He is founding chair of the Text Analytics pinnacle and principal consultant at Washington, D.C., based Alta Plana Corporation. Seth consults, writes, and speaks on information-systems strategy, data management and analysis systems, IT industry trends, and emerging analytical technologies. Seth chairs the Sentiment Analysis Symposium and the Text Analytics Summit.
Editor’s Note: More articles and resources are available in Seth's BeyeNETWORK Expert Channel. exist sure to visit today!
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Data scientists rely on tools/products/solutions to help them congregate insights from data. Gregory Piatetsky of KDNuggets conducts an annual survey of data data professionals to better understand the different types of tools they use. Here are the results of the 2015 survey. He followed his initial posting with additional analyses to better understand which tools accelerate together. In the latter posting, he looked at pairs of tools and create that some tools mind to accelerate together (usage of tools are correlated with each other). He offered the anonymized raw data set for free to cheer other people to analyze the data, which I did.Dimension Reduction through Principal Components Analysis
His approach looked at pairs of tools to understand their relationship with the other. I took a slightly different approach. I applied principal components analysis. The current approach groups the tools by looking at the relationship among outright tools simultaneously. In general, principal components analysis examines the statistical relationships (e.g., covariances) among a big set of variables and tries to account for these correlations using a smaller number of variables (components).
The results of the principal components analysis are presented in tabular format called the principal component matrix. The factor matrix is an NxM table (N = number of original variables and M = number of underlying components). The elements of a principal component matrix picture the relationship between each of the variables and the components. These elements picture the power of relationship between the variables and each of the underlying components. The results of the principal components analysis command us two things:
This consume of principal components analysis is exploratory in nature. That is, I didn’t impose a pre-defined structure on the data itself. The pattern of relationships among the 95 tools drove the pattern of results. While human judgment comes into play in the determination of the number of components that best report the data, the selection of the number of components is based on the results. The goal of the current analysis was to account for the relationship among the 95 tools with as few components as was necessary. Toward that end, there are a yoke of rules of thumb that I used to determine the number of components using the eigenvalues (output of principal components analysis). The first rule of thumb is to set the number of components based on the number of eigenvalues greater than union (1.0). Another way is to plot (called a scree plot) the 95 eigenvalues to identify a pellucid breaking point along the eigenvalues.
The plot of the eigenvalues appeared to smash around the 13th and 14th eigenvalue. Therefore, I chose a 13-factor solution to account for the relationships among the 95 data science tools.Table 1. Principal Component Matrix of 95 Data Science Tools – data from KDNuggets 2015 annual survey of data professionals. Click image to enlarge.
Based on a 13-factor solution, the principal component matrix (see Table 1) was kindly of smooth to interpret. Some of the cell values in the matrix in Table 1 are bold to picture values greater than .33. The components’ headings are based on the tools that loaded highest on that component. For example, four IBM products loaded highly on component 6, showing that usage of these tools by a given respondent mind to accelerate together (if you consume one of IBM’s tools, you mind to consume the other(s)); as a result, I labeled that component as IBM. Similarly, based on the tools that were highly related to the other 12 factors, the other 12 factors were labeled accordingly.Tool Groupings
The results imply that 13 tool grouping report the data. I’ve listed the groupings below and include the tools that report each grouping (if number of votes are greater than 20). Tools that plunge within a specific group mind to exist used together.
The consume of specific sizable Data, data mining and data science tools mind to occur together. Based on the current analysis of tool usage, the 90+ tools can exist grouped into a smaller subsets of tools. The results of the current analysis are kindly of consistent with the prior results. For example, Piatetsky create that Pig usage was closely associate with Hadoop, Spark, scikit-learn, Unix shell/awk/gawk and Python. In the current analysis, they create that Pig was likewise associated with Hadoop and Spark. However, they create that the consume of Pig was associated with HBase, Hive, Mahout, MLlib, Scala and SQL on Hadoop. It’s essential to note that the former analysis used the top 20 tools while the latter analysis used outright 90+ tools; this difference could account for the differences between the two analyses.
To improve your chances of success in your sizable Data projects, it’s essential that you select the birthright data tools. No separate tool will attain it all, and data professionals mind to consume more than one data-related tool (in this study, they create that, on average, data professionals consume 5 data tools). One way to help in your selection process is to identify the tools sets that other data professionals are using. The results imply that you respect looking at tools within components as potential candidates for tools you might consider.
Some of the tool groupings are simply based on the parent company of the tools, including IBM, Microsoft and SAS. Perhaps cross-selling data science tools is a lot easier within a major brand than it is across different brands. This makes sense to the extent that a company’s products likely work together better than with other vendors’ products. Still, more research is definitely needed to understand why inescapable tools mind to exist used together.
I’m interested in seeing what others find with these data. Here is the link to the anonymized data set (CSV format).
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