70-778 Analyzing and Visualizing Data with Power BI Exam Dumps Collected by Killexams.com Exam Dumps Updated On : Click To Check Update

Analyzing and Visualizing Data with Power BI book

the exhaust of vitality BI and SSRS for visualizing SQL Server and R records (part 4) | 70-778 Dumps and actual exam Questions with VCE drill Test

Visualizing statistics is vital half to realizing the dataset that they are attempting to analyses and a unique, pictoral view of the statistics. as a substitute of a tabular/matrix view or numerical views, a presentation in the benevolent of photographs, diagrams, and graphs can aid broaden facts insight. actually this brings the understanding of statistics to a brand new level.

to date, within the previous article they now contain mentioned how to anatomize earnings facts. And now and again, visualization is much obligatory. in this article, they will focus on two techniques visualizing the data. specifically:

With power BI

With reporting functions (SSRS)

With R apparatus for visible Studio / R Studio

vigour BI

For this matter, they can exhaust again the WideWorldImportersDW demo database and they will exhaust the visualization for clustering. let us seize here question:

DECLARE @SQLStat NVARCHAR(4000) SET @SQLStat = 'select SUM(fs.[Profit]) AS earnings ,c.[Sales Territory] AS SalesTerritory ,CASE WHEN c.[Sales Territory] = ''Rocky Mountain'' THEN 1 WHEN c.[Sales Territory] = ''Mideast'' THEN 2 WHEN c.[Sales Territory] = ''New England'' THEN three WHEN c.[Sales Territory] = ''Plains'' THEN 4 WHEN c.[Sales Territory] = ''Southeast'' THEN 5 WHEN c.[Sales Territory] = ''super Lakes'' THEN 6 WHEN c.[Sales Territory] = ''Southwest'' THEN 7 WHEN c.[Sales Territory] = ''a long artery West'' THEN 8 finish AS SalesTerritoryID ,fs.[Customer Key] AS CustomerKey ,SUM(fs.[Quantity]) AS amount FROM [Fact].[Sale] AS fs subsist a participate of dimension.metropolis AS c ON c.[City Key] = fs.[City Key] the place fs.[customer key] <> 0 AND c.[Sales Territory] not IN (''external'') neighborhood by means of c.[Sales Territory] ,fs.[Customer Key] ,CASE WHEN c.[Sales Territory] = ''Rocky Mountain'' THEN 1 WHEN c.[Sales Territory] = ''Mideast'' THEN 2 WHEN c.[Sales Territory] = ''New England'' THEN three WHEN c.[Sales Territory] = ''Plains'' THEN 4 WHEN c.[Sales Territory] = ''Southeast'' THEN 5 WHEN c.[Sales Territory] = ''super Lakes'' THEN 6 WHEN c.[Sales Territory] = ''Southwest'' THEN 7 WHEN c.[Sales Territory] = ''a long artery West'' THEN 8 conclusion ;' DECLARE @RStat NVARCHAR(4000) SET @RStat = 'library(ggplot2) image_file <- tempfile() jpeg(filename = image_file, width = four hundred, top = 400) clusters <- hclust(dist(revenue[,c(1,3,5)]), method = ''average'') clusterCut <- cutree(clusters, 3) ggplot(income, aes(complete, amount, colour = revenue$SalesTerritory)) + geom_point(alpha = 0.four, measurement = 2.5) + geom_point(col = clusterCut) + scale_color_manual(values = c(''black'', ''red'', ''eco-friendly'',''yellow'',''blue'',''lightblue'',''magenta'',''brown'')) dev.off() OutputDataSet <- information.frame(statistics=readBin(file(image_file, "rb"), what=uncooked(), n=1e6))' EXECUTE sp_execute_external_script @language = N'R' ,@script = @RStat ,@input_data_1 = @SQLStat ,@input_data_1_name = N'earnings' WITH effect units ((plot varbinary(max)))

This might subsist directly imported into vitality BI in a just a minute distinctive means. On one hand the data might subsist imported the usage of best a T-SQL query.

opt for SUM(fs.[Profit]) AS earnings ,c.[Sales Territory] AS SalesTerritory ,CASE WHEN c.[Sales Territory] = 'Rocky Mountain' THEN 1 WHEN c.[Sales Territory] = 'Mideast' THEN 2 WHEN c.[Sales Territory] = 'New England' THEN 3 WHEN c.[Sales Territory] = 'Plains' THEN four WHEN c.[Sales Territory] = 'Southeast' THEN 5 WHEN c.[Sales Territory] = 'extraordinary Lakes' THEN 6 WHEN c.[Sales Territory] = 'Southwest' THEN 7 WHEN c.[Sales Territory] = 'a ways West' THEN 8 conclusion AS SalesTerritoryID ,fs.[Customer Key] AS CustomerKey ,SUM(fs.[Quantity]) AS amount FROM [Fact].[Sale] AS fs link dimension.city AS c ON c.[City Key] = fs.[City Key] where fs.[customer key] <> 0 AND c.[Sales Territory] now not IN ('external') community with the aid of c.[Sales Territory] ,fs.[Customer Key] ,CASE WHEN c.[Sales Territory] = 'Rocky Mountain' THEN 1 WHEN c.[Sales Territory] = 'Mideast' THEN 2 WHEN c.[Sales Territory] = 'New England' THEN 3 WHEN c.[Sales Territory] = 'Plains' THEN 4 WHEN c.[Sales Territory] = 'Southeast' THEN 5 WHEN c.[Sales Territory] = 'great Lakes' THEN 6 WHEN c.[Sales Territory] = 'Southwest' THEN 7 WHEN c.[Sales Territory] = 'far West' THEN eight conclusion

And later one at a time the R code:

clusters <- hclust(dist(sales[,c(1,3,5)]), system = ''common'') clusterCut <- cutree(clusters, 3) ggplot(sales, aes(total, amount, colour = earnings$SalesTerritory)) + geom_point(alpha = 0.4, size = 2.5) + geom_point(col = clusterCut) + scale_color_manual(values = c(''black'', ''red'', ''eco-friendly'',''yellow'',''blue'',''lightblue'',''magenta'',''brown''))

After opening vigour BI, they elect regain information -> SQL Server and insert complete vital advice, as proven in the print screen beneath:

After clicking adequate, statistics will subsist imported into power BI. subsequent step is to opt for  “New visual” and on the visualizations record elect the R script visible.

You may regain a dialog window asking for enabling R visualization. After that, select the variables needed for the graph. in accordance with the R code, we're the exhaust of columns income, quantity and SalesTerritoryID. complete three columns will materialize in a predefined dataset as an information.body that the R visualization is developing by means of default:

within the R-script code they can paste the R code from the illustration above. starting with R code, they want some minor modifications – change the designation of dataset and rename the columns. So from this:

library(ggplot2) clusters <- hclust(dist(earnings[,c(1,3,5)]), formula = ''commonplace'') clusterCut <- cutree(clusters, 3) ggplot(income, aes(total, quantity, colour = sales$SalesTerritory)) + geom_point(alpha = 0.four, measurement = 2.5) + geom_point(col = clusterCut) + scale_color_manual(values = c(''black'', ''purple'', ''eco-friendly'',''yellow'',''blue'',''lightblue'',''magenta'',''brown''))

into this:

library(ggplot2) clusters <- hclust(dist(dataset[,c(1,2,3)]), components = 'commonplace') clusterCut <- cutree(clusters, 3) ggplot(dataset, aes(earnings, volume, colour = dataset$SalesTerritory)) + geom_point(alpha = 0.four, measurement = 2.5) + geom_point(col = clusterCut) + scale_color_manual(values = c('black', 'crimson', 'green','yellow','blue','lightblue','magenta','brown'))

also, Make confident you check the costs or double quotes around the declared values in R code. After that, you'll regain a visualization in energy BI:

additionally, any variety of other R graph / visualization may too subsist introduced. for this intuition I actually contain determined so as to add a boxplot on income per revenue territory, the exhaust of R visualizer. So adding additional information to the cluster evaluation with boxplot will provide end-person further perception of how profit is spread among sales territories.

The graph is got using birthright here R code:

with the aid of doing so, what they necessity in the final step is so as to add some facts slicers, to subsist able to dynamically refresh the data on both R visualizations. Of route, every other pre-prepared visualization accessible in energy BI can additionally exhaust the capabilities of information slicers. I added two slicers:  volume and revenue Territory. i can select (or multi-choose) the values and according to my decisions complete graphs which are in accordance with dataset the exhaust of these slicers might subsist automatically up to date.

The finish product can resemble a dashboard or a document or a playground for data scientist, records wranglers or any one interested to regain insight on the statistics set:

I brought the R Language emblem just to disclose that your company brand will too subsist added as neatly. The comprehensive vigour BI workbook is too obtainable for download.

if you wish to effect extra superior analytics on the imported dataset, the plot are always extra visuals available on the url handle: https://app.powerbi.com/visuals/ . the entire additional visuals can too subsist downloaded and introduced into your vitality BI booklet. There are also  R-powered visuals to subsist downloaded and ready to subsist used. For this text, I actually contain determined to down load further visual Chord:

And exhaust it in present e-book, via importing it:

And populate it with information with earnings and revenue Territory to recognize the distribution of earnings by means of territory.

again, the photograph tells greater than numbers, but Make confident not to overdo on the visuals or create non-sense graphs which might cause people to subsist stuck knowing the graph, as a substitute of assisting them subsist aware.

I actually contain delivered and made comparison for affiliation rules; really just assessment between the visualizations. i am simply including the ultimate comparison from energy BI ebook, the repose that you can comply with in the energy BI ebook. The R code is in reality the identical because the R code in archaic article, where I originally mentioned association suggestions. birthright here is the last define of the comparison of two visuals: R code visible and association guidelines visible.

well-nigh, both are in accordance with equal R packages (arules, aRulesVisual), simply that graph on left hand aspect to subsist configured through code and the outlook can too subsist modified birthright down to final element, whereas, graph on birthright hand side is embedded visual, too in line with R, with complete of the parameters construct in to subsist installation in power BI.

an additional very crucial factor and extremely positive method to import in energy BI are too R records.frames, which are desk presentation of the information. now and again, if you occur to are doing any superior analytics or visualizations, you may too want to add some additional info that can not subsist study from the graph. as an instance, let’s seize the clustering graph; cluster businesses are very property and visual, however a person who is extra into information would want to regain some data to this clustering as neatly. in this case, they will exhaust R visual once again, however maneuver and wrangle the outputted records into the dataframe and contain it characterize as a desk.

For cluster evaluation, I contain added the variety of occurrences for each and every customer in income territory wherein cluster (1, 2 or three) is appearing. desk is just a part presentation of graph.

The table has been generated with here R code in vigour BI:

library(gridExtra) clusters <- hclust(dist(dataset[,c(1,2,3)]), components = 'regular') clusterCut <- cutree(clusters, three) df <- records.body(table(clusterCut, dataset$SalesTerritory)) grid.desk(df)

once more, this desk will automatically replace, based on chosen criteria within the slicers, which comes very convenient when analyzing facts.

As you can see, I contain used the apparatus gridExtra, very efficacious kit to serve the level of plotting the tables with records extracted from R datasets.

Reporting capabilities (SSRS)

Reporting functions has been round very lengthy, so i will not recede into the reporting details. but the entire R visualizations available in vitality BI can even subsist implemented and utilized in SSRS. Reporting features brings additionally an further purposeful and valuable feature: choices. power BI offers you the slicers that may, in line with alternative, dynamically update the graphs, records and visualizations in R script, that may even subsist achieved with choices in SSRS. but what SSRS makes it possible for is, to add any extra parameter into the code, making R Language through SSRS even more bendy to the finish consumer. i'll justify this on an instance with the clustering analysis from already mentioned case (and habitual from archaic article).

When growing new report and defining dataset, replica/pasting the R code into the question text:

will recrudesce – every time document might subsist achieved – an error and the textboxes to populate the values of the entire parameters mandatory in order to execute externa method sp_execute_external_script. So, the stronger (if not the most reliable) artery to hold away from this, is conveniently to rescue the entire code as a stored system.

CREATE system ClusterAnalysis_Plot AS DECLARE @SQLStat NVARCHAR(4000) SET @SQLStat = 'choose SUM(fs.[Profit]) AS earnings ,c.[Sales Territory] AS SalesTerritory ,CASE WHEN c.[Sales Territory] = ''Rocky Mountain'' THEN 1 WHEN c.[Sales Territory] = ''Mideast'' THEN 2 WHEN c.[Sales Territory] = ''New England'' THEN three WHEN c.[Sales Territory] = ''Plains'' THEN four WHEN c.[Sales Territory] = ''Southeast'' THEN 5 WHEN c.[Sales Territory] = ''awesome Lakes'' THEN 6 WHEN c.[Sales Territory] = ''Southwest'' THEN 7 WHEN c.[Sales Territory] = ''a ways West'' THEN 8 finish AS SalesTerritoryID ,fs.[Customer Key] AS CustomerKey ,SUM(fs.[Quantity]) AS volume FROM [Fact].[Sale] AS fs subsist participate of dimension.city AS c ON c.[City Key] = fs.[City Key] the place fs.[customer key] <> 0 AND c.[Sales Territory] now not IN (''exterior'') community by artery of c.[Sales Territory] ,fs.[Customer Key] ,CASE WHEN c.[Sales Territory] = ''Rocky Mountain'' THEN 1 WHEN c.[Sales Territory] = ''Mideast'' THEN 2 WHEN c.[Sales Territory] = ''New England'' THEN three WHEN c.[Sales Territory] = ''Plains'' THEN four WHEN c.[Sales Territory] = ''Southeast'' THEN 5 WHEN c.[Sales Territory] = ''awesome Lakes'' THEN 6 WHEN c.[Sales Territory] = ''Southwest'' THEN 7 WHEN c.[Sales Territory] = ''a long artery West'' THEN 8 finish ;' DECLARE @RStat NVARCHAR(4000) SET @RStat = 'library(ggplot2) image_file <- tempfile() jpeg(filename = image_file, width = four hundred, top = 400) clusters <- hclust(dist(revenue[,c(1,3,5)]), formula = ''typical'') clusterCut <- cutree(clusters, three) ggplot(earnings, aes(profit, quantity, colour = earnings$SalesTerritory)) + geom_point(alpha = 0.four, dimension = 2.5) + geom_point(col = clusterCut) + scale_color_manual(values = c(''black'', ''crimson'', ''green'',''yellow'',''blue'',''lightblue'',''magenta'',''brown'')) dev.off() OutputDataSet <- data.frame(data=readBin(file(image_file, "rb"), what=uncooked(), n=1e6))' EXECUTE sp_execute_external_script @language = N'R' ,@script = @RStat ,@input_data_1 = @SQLStat ,@input_data_1_name = N'revenue' WITH influence units ((plot varbinary(max)));

and then you effectively add the process.

On record canvas, you add picture and effect the following homes:

Now retailer, (install) and Execute the document  in Reporting provider. you should note a chummy graph in SSRS.

using saved methods in SSRS is a extremely productive artery to visualize the information. using saved techniques that you would subsist able to additionally implement the parameters that without retard inject some values or chunk of codes to Make your visualizations greater dynamic. moreover that, producing tables is plenty less difficult finished in evaluation to vitality BI, but if you are looking to extract information from R consequences, subsist confident you complete the time recrudesce the R consequences to a learning body. information cadaver is a data classification, that R and SQL Server can operate with each and every other.

R apparatus for visual Studio / R Studio

one artery to imagine the records is to regain information into your RTVS or R Studio the plot that you would subsist able to visualize information. continually this can too subsist finished by storing your records from SQL Server into any of those two courses. one artery to effect it's to Make exhaust of ODBC driver. Very advantageous and powerful is accessible in kit RODBC. The very straightforward syntax is:

library(RODBC) myconn <-odbcDriverConnect("driver=SQL Server;Server=Srv_Tomaz;database=WideWorldImportersDW;trusted_connection=true") mydata <- sqlQuery(myconn, "opt for * FROM [Fact].[Order]") close(myconn)

After working this R Code, you might regain the total fact table into your R environment.  Now working on any sort of visualization is relatively easy.

Please word, in case you can subsist using larger dataset and importing records into R ambiance, with RODBC equipment, you may additionally adventure recollection obstacles. In such situations, i would strongly recommend the usage of RevoScaleR kit, that solves recollection hindrance issues!

Conclusion

records visualization is a crucial participate of information analysis, facts presentation and facts comprehension. complete three apparatus are a method how to assist an information wrangled, information scientist or statistics analyst to address and to deal with plotting facts. there are lots of alternative ways, and third celebration equipment, that allows for you to deepen the information perception, just result a simple rule, when using visuals: statistics visible necessity to clarify and broaden the statistics understanding. If this fundamental rule is not satisfied, definitely you're doing anything wrong. I didn't recede into the concept of visualization, given that this was now not my point, however I strongly recommend you to effect it. Very decent region to birth is statistics Visualization Catalogue.

author: Tomaz Kastrun (tomaz.kastrun@gmail.com)

Twitter: @tomaz_tsql

weblog: http://tomaztsql.wordpress.com

While it is hard errand to pick solid certification questions/answers assets regarding review, reputation and validity since individuals regain sham because of picking incorrectly benefit. Killexams.com ensure to serve its customers best to its assets as for exam dumps update and validity. The greater participate of other's sham report objection customers approach to us for the brain dumps and pass their exams cheerfully and effortlessly. They never deal on their review, reputation and property because killexams review, killexams reputation and killexams customer certainty is imperative to us. Extraordinarily they deal with killexams.com review, killexams.com reputation, killexams.com sham report grievance, killexams.com trust, killexams.com validity, killexams.com report and killexams.com scam. On the off desultory that you note any indecorous report posted by their rivals with the designation killexams sham report grievance web, killexams.com sham report, killexams.com scam, killexams.com protestation or something dote this, simply recall there are constantly terrible individuals harming reputation of cogent administrations because of their advantages. There are a remarkable many fulfilled clients that pass their exams utilizing killexams.com brain dumps, killexams PDF questions, killexams braindumps questions, killexams exam simulator. Visit Killexams.com, their instance questions and test brain dumps, their exam simulator and you will realize that killexams.com is the best brain dumps site.

---

HC-611 braindumps | 72-642 questions and answers | 9L0-063 dumps | M2090-626 pdf get | HP0-J17 bootcamp | CIA-II mock exam | 77-882 drill test | EMT exam prep | GE0-803 drill questions | 70-345 actual questions | C8010-250 braindumps | TB0-105 test prep | LOT-408 brain dumps | EX0-105 drill test | HP0-427 drill Test | 1Z0-134 questions and answers | E20-060 free pdf get | F50-526 free pdf | NS0-151 cram | C2020-703 brain dumps |

---

---

E20-562 questions and answers | 090-056 dump | GB0-183 drill questions | CAT-120 free pdf | 00M-664 braindumps | HP2-B103 dumps questions | HP0-780 exam prep | PCNSE sample test | 050-649 braindumps | C4040-120 mock exam | HP2-W100 bootcamp | HP0-S32 test questions | S10-110 free pdf | HP0-P24 VCE | HPE0-S46 brain dumps | 270-551 drill exam | 000-048 dumps | COG-605 braindumps | PW0-205 drill Test | 000-432 brain dumps |

---

View Complete list of Killexams.com Certification exam dumps

---

70-551-CSharp actual questions | NS0-502 actual questions | 500-290 drill test | 1Z0-466 VCE | NCBTMB brain dumps | A2040-913 test questions | HP2-H20 study guide | 156-915-80 braindumps | C2030-280 free pdf | 190-737 questions and answers | 1Z0-105 questions answers | HP0-M77 study guide | 000-970 drill Test | HP0-068 test prep | 190-273 dumps | HP0-085 free pdf | HP0-T01 bootcamp | MD0-235 drill test | 9A0-154 examcollection | ISEB-BA1 questions and answers |

---

---

List of Certification exam Dumps

3COM [8 Certification Exam(s) ]
AccessData [1 Certification Exam(s) ]
ACFE [1 Certification Exam(s) ]
ACI [3 Certification Exam(s) ]
Acme-Packet [1 Certification Exam(s) ]
ACSM [4 Certification Exam(s) ]
ACT [1 Certification Exam(s) ]
Admission-Tests [13 Certification Exam(s) ]
ADOBE [93 Certification Exam(s) ]
AFP [1 Certification Exam(s) ]
AICPA [2 Certification Exam(s) ]
AIIM [1 Certification Exam(s) ]
Alcatel-Lucent [13 Certification Exam(s) ]
Alfresco [1 Certification Exam(s) ]
Altiris [3 Certification Exam(s) ]
Amazon [7 Certification Exam(s) ]
American-College [2 Certification Exam(s) ]
Android [4 Certification Exam(s) ]
APA [1 Certification Exam(s) ]
APC [2 Certification Exam(s) ]
APICS [2 Certification Exam(s) ]
Apple [71 Certification Exam(s) ]
AppSense [1 Certification Exam(s) ]
APTUSC [1 Certification Exam(s) ]
Arizona-Education [1 Certification Exam(s) ]
ARM [1 Certification Exam(s) ]
Aruba [8 Certification Exam(s) ]
ASIS [2 Certification Exam(s) ]
ASQ [3 Certification Exam(s) ]
ASTQB [8 Certification Exam(s) ]
Autodesk [2 Certification Exam(s) ]
Avaya [106 Certification Exam(s) ]
AXELOS [1 Certification Exam(s) ]
Axis [1 Certification Exam(s) ]
Banking [1 Certification Exam(s) ]
BEA [5 Certification Exam(s) ]
BICSI [2 Certification Exam(s) ]
BlackBerry [17 Certification Exam(s) ]
BlueCoat [2 Certification Exam(s) ]
Brocade [4 Certification Exam(s) ]
Business-Objects [11 Certification Exam(s) ]
Business-Tests [4 Certification Exam(s) ]
CA-Technologies [20 Certification Exam(s) ]
Certification-Board [10 Certification Exam(s) ]
Certiport [3 Certification Exam(s) ]
CheckPoint [44 Certification Exam(s) ]
CIDQ [1 Certification Exam(s) ]
CIPS [4 Certification Exam(s) ]
Cisco [321 Certification Exam(s) ]
Citrix [48 Certification Exam(s) ]
CIW [18 Certification Exam(s) ]
Cloudera [10 Certification Exam(s) ]
Cognos [19 Certification Exam(s) ]
College-Board [2 Certification Exam(s) ]
CompTIA [79 Certification Exam(s) ]
ComputerAssociates [6 Certification Exam(s) ]
Consultant [2 Certification Exam(s) ]
Counselor [4 Certification Exam(s) ]
CPP-Institute [4 Certification Exam(s) ]
CSP [1 Certification Exam(s) ]
CWNA [1 Certification Exam(s) ]
CWNP [14 Certification Exam(s) ]
CyberArk [2 Certification Exam(s) ]
Dassault [2 Certification Exam(s) ]
DELL [13 Certification Exam(s) ]
DMI [1 Certification Exam(s) ]
DRI [1 Certification Exam(s) ]
ECCouncil [23 Certification Exam(s) ]
ECDL [1 Certification Exam(s) ]
EMC [128 Certification Exam(s) ]
Enterasys [13 Certification Exam(s) ]
Ericsson [5 Certification Exam(s) ]
ESPA [1 Certification Exam(s) ]
Esri [2 Certification Exam(s) ]
ExamExpress [15 Certification Exam(s) ]
Exin [40 Certification Exam(s) ]
ExtremeNetworks [3 Certification Exam(s) ]
F5-Networks [20 Certification Exam(s) ]
FCTC [2 Certification Exam(s) ]
Filemaker [9 Certification Exam(s) ]
Financial [36 Certification Exam(s) ]
Food [4 Certification Exam(s) ]
Fortinet [16 Certification Exam(s) ]
Foundry [6 Certification Exam(s) ]
FSMTB [1 Certification Exam(s) ]
Fujitsu [2 Certification Exam(s) ]
GAQM [9 Certification Exam(s) ]
Genesys [4 Certification Exam(s) ]
GIAC [15 Certification Exam(s) ]
Google [5 Certification Exam(s) ]
GuidanceSoftware [2 Certification Exam(s) ]
H3C [1 Certification Exam(s) ]
HDI [9 Certification Exam(s) ]
Healthcare [3 Certification Exam(s) ]
HIPAA [2 Certification Exam(s) ]
Hitachi [30 Certification Exam(s) ]
Hortonworks [4 Certification Exam(s) ]
Hospitality [2 Certification Exam(s) ]
HP [753 Certification Exam(s) ]
HR [4 Certification Exam(s) ]
HRCI [1 Certification Exam(s) ]
Huawei [31 Certification Exam(s) ]
Hyperion [10 Certification Exam(s) ]
IAAP [1 Certification Exam(s) ]
IAHCSMM [1 Certification Exam(s) ]
IBM [1535 Certification Exam(s) ]
IBQH [1 Certification Exam(s) ]
ICAI [1 Certification Exam(s) ]
ICDL [6 Certification Exam(s) ]
IEEE [1 Certification Exam(s) ]
IELTS [1 Certification Exam(s) ]
IFPUG [1 Certification Exam(s) ]
IIA [3 Certification Exam(s) ]
IIBA [2 Certification Exam(s) ]
IISFA [1 Certification Exam(s) ]
Intel [2 Certification Exam(s) ]
IQN [1 Certification Exam(s) ]
IRS [1 Certification Exam(s) ]
ISA [1 Certification Exam(s) ]
ISACA [4 Certification Exam(s) ]
ISC2 [6 Certification Exam(s) ]
ISEB [24 Certification Exam(s) ]
Isilon [4 Certification Exam(s) ]
ISM [6 Certification Exam(s) ]
iSQI [7 Certification Exam(s) ]
ITEC [1 Certification Exam(s) ]
Juniper [66 Certification Exam(s) ]
LEED [1 Certification Exam(s) ]
Legato [5 Certification Exam(s) ]
Liferay [1 Certification Exam(s) ]
Logical-Operations [1 Certification Exam(s) ]
Lotus [66 Certification Exam(s) ]
LPI [24 Certification Exam(s) ]
LSI [3 Certification Exam(s) ]
Magento [3 Certification Exam(s) ]
Maintenance [2 Certification Exam(s) ]
McAfee [9 Certification Exam(s) ]
McData [3 Certification Exam(s) ]
Medical [68 Certification Exam(s) ]
Microsoft [387 Certification Exam(s) ]
Mile2 [3 Certification Exam(s) ]
Military [1 Certification Exam(s) ]
Misc [1 Certification Exam(s) ]
Motorola [7 Certification Exam(s) ]
mySQL [4 Certification Exam(s) ]
NBSTSA [1 Certification Exam(s) ]
NCEES [2 Certification Exam(s) ]
NCIDQ [1 Certification Exam(s) ]
NCLEX [3 Certification Exam(s) ]
Network-General [12 Certification Exam(s) ]
NetworkAppliance [39 Certification Exam(s) ]
NI [1 Certification Exam(s) ]
NIELIT [1 Certification Exam(s) ]
Nokia [6 Certification Exam(s) ]
Nortel [130 Certification Exam(s) ]
Novell [37 Certification Exam(s) ]
OMG [10 Certification Exam(s) ]
Oracle [299 Certification Exam(s) ]
P&C [2 Certification Exam(s) ]
Palo-Alto [4 Certification Exam(s) ]
PARCC [1 Certification Exam(s) ]
PayPal [1 Certification Exam(s) ]
Pegasystems [12 Certification Exam(s) ]
PEOPLECERT [4 Certification Exam(s) ]
PMI [16 Certification Exam(s) ]
Polycom [2 Certification Exam(s) ]
PostgreSQL-CE [1 Certification Exam(s) ]
Prince2 [7 Certification Exam(s) ]
PRMIA [1 Certification Exam(s) ]
PsychCorp [1 Certification Exam(s) ]
PTCB [2 Certification Exam(s) ]
QAI [1 Certification Exam(s) ]
QlikView [1 Certification Exam(s) ]
Quality-Assurance [7 Certification Exam(s) ]
RACC [1 Certification Exam(s) ]
Real Estate [1 Certification Exam(s) ]
Real-Estate [1 Certification Exam(s) ]
RedHat [8 Certification Exam(s) ]
RES [5 Certification Exam(s) ]
Riverbed [8 Certification Exam(s) ]
RSA [15 Certification Exam(s) ]
Sair [8 Certification Exam(s) ]
Salesforce [5 Certification Exam(s) ]
SANS [1 Certification Exam(s) ]
SAP [98 Certification Exam(s) ]
SASInstitute [15 Certification Exam(s) ]
SAT [1 Certification Exam(s) ]
SCO [10 Certification Exam(s) ]
SCP [6 Certification Exam(s) ]
SDI [3 Certification Exam(s) ]
See-Beyond [1 Certification Exam(s) ]
Siemens [1 Certification Exam(s) ]
Snia [7 Certification Exam(s) ]
SOA [15 Certification Exam(s) ]
Social-Work-Board [4 Certification Exam(s) ]
SpringSource [1 Certification Exam(s) ]
SUN [63 Certification Exam(s) ]
SUSE [1 Certification Exam(s) ]
Sybase [17 Certification Exam(s) ]
Symantec [136 Certification Exam(s) ]
Teacher-Certification [4 Certification Exam(s) ]
The-Open-Group [8 Certification Exam(s) ]
TIA [3 Certification Exam(s) ]
Tibco [18 Certification Exam(s) ]
Trainers [3 Certification Exam(s) ]
Trend [1 Certification Exam(s) ]
TruSecure [1 Certification Exam(s) ]
USMLE [1 Certification Exam(s) ]
VCE [7 Certification Exam(s) ]
Veeam [2 Certification Exam(s) ]
Veritas [33 Certification Exam(s) ]
Vmware [63 Certification Exam(s) ]
Wonderlic [2 Certification Exam(s) ]
Worldatwork [2 Certification Exam(s) ]
XML-Master [3 Certification Exam(s) ]
Zend [6 Certification Exam(s) ]

---

References :

Box.net : https://app.box.com/s/v4oew0iwpgid9xnvzxc7g42z1v1vrqob
zoho.com : https://docs.zoho.com/file/67jzb1e92f64080914144ad5c7bb21981d8fb
Calameo : http://en.calameo.com/books/0049235263b14fbf4f712
MegaCerts.com Certification exam dumps