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M2040-641 - IBM Exceptional Web Experience Sales Mastery Test v1 - Dump Information

Vendor : IBM
Exam Code : M2040-641
Exam Name : IBM Exceptional Web Experience Sales Mastery Test v1
Questions and Answers : 50 Q & A
Updated On : December 10, 2018
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M2040-641 IBM Exceptional Web Experience Sales Mastery Test v1

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M2040-641 exam Dumps Source : IBM Exceptional Web Experience Sales Mastery Test v1

Test Code : M2040-641
Test Name : IBM Exceptional Web Experience Sales Mastery Test v1
Vendor Name : IBM
Q&A : 50 Real Questions

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IBM IBM Exceptional Web Experience

Is Nagios The way forward for Monitoring For IBM i? | killexams.com Real Questions and Pass4sure dumps

November 12, 2018 Alex Woodie

For a long time, know-how gurus turned to established frameworks from IBM Tivoli, CA, Hewlett Packard, and BMC (“The large four”) to monitor their hardware and software stacks. however the open supply world has caught up with those closed monitoring environments, and a project dubbed Nagios is poised to be the go-to platform for IT monitoring, together with on IBM i.

Nagios, in case you aren't typical, is a free and open supply software product that provides monitoring and alerting for servers, network apparatus, functions, and the array of functions that organizations increasingly count on. The utility –backed by using the mandatory recursive acronym “Nagios Ain’t Gonna Insist On Sainthood” – become firstly developed through Ethan Galstad lower back in 2002 to run and computer screen Linux programs, which was just beginning to make headway in business facts facilities.

through the years, the C-based mostly application has been prolonged to guide an array of object varieties, including host supplies like processor load, disk and RAM utilization, and device logs for a majority of commonplace working programs, including IBM i. The full of life Nagios neighborhood has created a wide array of Nagios agents which have extended the framework to an estimated 5,000 instruments.

Nagios is an open supply device that allows for administrators to display screen their IT apparatus and purposes.

On the network facet of issues, Nagios Core (because the open supply product is known) screens routers, switches, and other apparatus, and supports SMTP, POP3, FTP, and SNMP protocols, among others. All far flung monitoring can be encrypted, and it additionally offers a plug-in that lets users create their personal monitors in lots of languages.

information collected through lively and passive Nagios plug-ins is routed into the Nagios server, where the facts is sorted and signals are despatched out. clients can consume indicators in numerous methods, including through a web browser, through SMS pagers, and thru electronic mail. With a simple look on the Nagios dashboard on a phone, a methods admins can see if important servers, process, and services are alive or lifeless.

The Nagios Core server application can also work with a “round-robin database” (RRD) to simplify the storage and querying of time-series data. With RRD, admins can dive deeper into Nagios records and think about graphs to look performance traits. And with a little setup ahead of time, Nagios may also be configured to immediately respond to pursuits as they take place, or enhance alerts to different people.

businesses that want more than what Nagios Core has to offer can discover it from Nagios businesses, the industrial outfit behind the open source challenge. The St. Paul, Minnesota-based enterprise, which employs Galstad, extends Nagios Core with a number of offerings, together with Nagio XI, which points a greater extensible front-conclusion and a MySQL-primarily based returned-conclusion. Nagios XI additionally brings a much better user experience with greater effective graphs and more suitable dashboards.

IBM i clients can use Nagios to display screen 15 metrics with the Nagios Plug-Ins for IBM i beta.

alas, Nagios businesses doesn’t support IBM i. however you could get a Nagios distribution for IBM i from a bit outfit known as international company Machines. In 2017, massive Blue shipped a beta version of an IBM i plug-in designed to feed information from the IBM i sever into the open source Nagios Core product or Nagios XI.

in response to a developerWorks web page, the IBM i Nagios plug-in collects 15 diverse facts aspects from IBM i servers, including things like CPU and disk utilization, ASP usage, variety of active jobs, and long-running SQL jobs, among others. Some of those capabilities are supported by way of SNMP, while others require the open source JTOpen Java toolbox to be put in.

The Nagios server itself doesn’t run on IBM i – at least not yet. With the Nagios on IBM i plug-in, IBM offers clients with guidelines on a way to set up Nagios Core or Nagios XI on a Linux server. Technically, there should be nothing stopping from a consumer installation Nagios in a Linux LPAR on the vigor systems server – and even for IBM to port the application to the IBM i OS via PASE – however that has no longer took place yet.

IBM makes the case for IBM i retail outlets to use Nagios in a PDF presentation on Nagios created by using IBM i business architect Tim Rowe and Wang Yun, who developed the Nagios for IBM i plug-in. whereas Navigator for i provides first rate insurance of IBM i-centric queues and metrics, that product doesn’t provide customers with any visibility of what’s happening outside the IBM i device.

purchasers who purchase Nagios XI can computer screen IBM i metrics graphically.

Nagios, in spite of this, gives administrators and operators with a single centralized view of all IT belongings, Rowe and Yun write. besides the core IBM i metrics that at the moment are purchasable by the use of the Nagios plug-in, IBM i clients can get fashion and historical data, as well as the flexibility to configure metrics to their liking, now not to point out the potential to create their personal customized plug-ins.

IBM isn’t the handiest enterprise doing Nagios work on IBM i. a number of years in the past, ShapPin Cheng launched a GitHub mission called check_as400 that moved information from IBM i server logs into Nagios. due to the fact the extensibility and openness of Nagios, it wouldn’t be mind-blowing to look impartial application companies in the IBM i neighborhood adopt the know-how for their personal techniques monitoring choices.

For now, IBM offers the Nagios plug-in as a beta. Don’t be surprised to see it become a totally supported providing within the months to come back, specially since the love affair that IBM has with open source software nowadays.

related reports

IBM i efficiency secrets and techniques printed

What’s Cooking With IBM i On GitHub?

ASCI Job Scheduler receives Hooks for Nagios


IBM Cloud continues to exhibit design excellence | killexams.com Real Questions and Pass4sure dumps

The IBM Cloud design group is delighted to announce that two of our items, IBM statistics Science experience (DSX) and IBM App connect, have bought an iF Design Award 2018 within the Communications — application application class. each year, the area’s oldest independent design firm, iF international discussion board Design GmbH, organizes the iF Design Award. For 65 years, the iF Design Award has been recognized as an arbiter of exceptional for top notch design.

IBM DSX and IBM App connect won over the sixty three-member jury, made of impartial experts from in every single place the world, with their user-focused experience design for business application. The competition became extreme: over 6,400 entries were submitted from 54 countries in hopes of receiving the seal of quality.

This award is an additional success to 2 different design awards recently given to IBM Cloud, the pink Dot Award and the Spark Award, and serves as an unequivocal indicator of the nice of labor produced with the aid of IBM Design and how much design has come to influence the entire corporation.

The successful items

IBM App connect is a cloud-based mostly answer for enterprise users that right now connects apps to automate tasks and increase productivity. in its place of manually performing high-touch, repetitive integration initiatives, it offers clients an easy, business-oriented interface to create workflows and get notifications, sync facts, music results and more. company choice makers that wish to integrate their enterprise apps and combine their records often don’t have a straightforward solution to accomplish that. They both write customized code or use advanced integration systems, which is time consuming, includes loads of software and requires deep middleware abilities. IBM App join changed into designed to enable clients to seamlessly connect and integrate with again-conclusion techniques, web, and cell purposes anyplace they reside — no matter if on-premises or in a non-public or public cloud.

we are smitten by growing extraordinary experiences for our users, and it’s remarkable being a part of an eclectic team working together to make this a fact!” — Sarah Burwood, Design Lead & UX dressmaker

From a design viewpoint, the IBM App join venture provided a thrilling possibility to re-imagine the integration experience for brand new clients, and follow design pondering to this business context.

“My proudest recollections of our App connect event naturally centre around the designers. As valued clientele reacted to what we’d made, they followed and listened; then the total IBM crew moved as one to iterate and raise that person adventure.” — Brian Peaston, IBM Design supervisor, software Integration

IBM App connect

IBM facts Science experience (DSX) is a cloud-based, imaginative, end-to-end experience for data scientists to research, create, and collaborate across multidisciplinary groups. DSX merges a powerful set of open supply and legacy tools with a web community for information scientists. at the time of its inception, there wasn’t a unified platform attainable to information practitioners. Our simple mission changed into to make information simple and available via our person-founded design system. The information science box is complex and constantly changing. DSX additionally continues to extend with the container, incorporating new, richer technologies as statistics scientists’ workflow and tools shift.

“facts Science adventure is a real innovation, merging an impressive set of tools with an online community. There are no limitations between growing, getting to know and sharing.” — David Townsend, Director of Design (IBM Analytics)

IBM facts Science eventIBM Design Takes a number one function in commercial enterprise application Experiences

commercial enterprise software is commonly looked at because the roach hotel of complicated and clunky user experiences, far faraway from the contemporary, stylish and intuitive person experiences attainable in lots of buyer apps. however, “the instances they're a-changin” as agencies are starting to recognize how UX can basically be a key differentiator within the business software business. There’s a becoming recognition that companies need to offer enterprise and business software that works as neatly and as intuitively because the different apps that their employees use of their day by day lives.

enterprise application wants product experiences that boost worker engagement, simplify advanced workflows, cut back turnover costs, dispose of the need for training, and most significantly, increase user pride and worker productiveness.

As a leader within the enterprise application field, IBM has the ability to set a global precedent of how design can impact items, users, and businesses on a big scale. At IBM Design, we're supplying on that promise to deliver attractive back to business utility.

The four design awards for IBM Cloud products in the past year, together with these two from iF Design, display the unbelievable strides that IBM has made as a design-driven company, as smartly as the critical function that design plays in IBM’s cloud products. We believe that endured and unwavering focus on our users, and on the design fine and consumer event of our products will enable IBM Cloud to continue to excel, set precedents and differentiate by way of design.

Awardees:

IBM DSXDirector of Design: David Townsend (IBM Analytics, San Francisco)DSX Design group: Caroline law, Renee Mascarinas, Jessica Gore, Leila Johannesen (IBM Analytics, San Francisco)

IBM App ConnectDesign supervisor: Brian PeastonApp join Design group: Sarah Burwood, Gary Thornton, Rob Breeds, Danny Skinner, Lee Chase and Steve Haskey.


SAP joins a growing to be checklist of application giants making massive acquisitions in 2018: here's a full rundown | killexams.com Real Questions and Pass4sure dumps

Adobe CEO Shantanu Narayen, Microsoft CEO Satya Nadella and SAP CEO Bill McDermott announce the Open Data Initiative at Microsoft's 2018 Ignite conference in Orlando, Florida.

Screenshot | Microsoft reside stream

Adobe CEO Shantanu Narayen, Microsoft CEO Satya Nadella and SAP CEO bill McDermott announce the Open records Initiative at Microsoft's 2018 Ignite conference in Orlando, Florida.

Legacy tech corporations were scooping up smaller cloud and application providers in big deals all through 2018.

The consolidation comes as older business tech businesses try to stay primary against the juggernaut of Amazon internet features, in addition to Google's smartly-funded cloud play and a rising crop of nimble undertaking-backed start-ups.

On Sunday, SAP grew to become the newest to enter the fray, paying $eight billion in cash for survey application enterprise Qualtrics almost immediately before it planned to move public.

SAP is in good company. here are one of the vital different colossal offers accomplished through large commercial enterprise gamers this 12 months:


M2040-641 IBM Exceptional Web Experience Sales Mastery Test v1

Study Guide Prepared by Killexams.com IBM Dumps Experts


Killexams.com M2040-641 Dumps and Real Questions

100% Real Questions - Exam Pass Guarantee with High Marks - Just Memorize the Answers



M2040-641 exam Dumps Source : IBM Exceptional Web Experience Sales Mastery Test v1

Test Code : M2040-641
Test Name : IBM Exceptional Web Experience Sales Mastery Test v1
Vendor Name : IBM
Q&A : 50 Real Questions

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The Best Self-Service Business Intelligence (BI) Tools of 2018 | killexams.com real questions and Pass4sure dumps

Analytics Beyond Spreadsheets

For many years, Microsoft Excel and other spreadsheets were the tools of choice for business professionals who were looking to visualize their data. But spreadsheets had their limits for many business intelligence (BI)-related tasks. Even today, trying to creating charts analyzing complex datasets in Excel can still be frustrating. Sometimes you start with the wrong kind of data, for example, or you may not know how to manipulate the spreadsheet to create the data visualization{{/ZIFFARTICLE} you need. On the other hand, the rising tide of data democratization is giving everyone in an organization access to corporate data. The need has arisen for effective tools that people of all skill levels can use to make sense of the wealth of information created by businesses every single day.

Spreadsheets also fall down when the data isn't well-structured or can't be sorted out in neat rows and columns. And, if you have millions of rows or very sparse matrices, then the data in a spreadsheet can be painful to enter and it can be hard to visualize your data. Spreadsheets also have issues if you are trying to create a report that spans multiple data tables or that mixes in Structured Query Language (SQL)-based databases, or when multiple users try to maintain and collaborate on the same spreadsheet.

A spreadsheet containing up-to-the-minute data can also be a problem, particularly if you have exported graphics that need to be refreshed when the data changes. Finally, spreadsheets aren't good for data exploration; trying to spot trends, outlying data points, or counterintuitive results is difficult when what you are looking for is often hidden in a long row of numbers.

While spreadsheets and self-service BI tools both make use of tables of numbers, they are really acting in different arenas with different purposes. A spreadsheet is first and foremost a way to store and display calculations. While some spreadsheets can create very sophisticated mathematical models, at their core it is all about the math more than the model itself.

This is all a long-winded way of saying that when businesses use a spreadsheet, they are actively sabotaging themselves and their ability to consistently get valuable insights from their data. BI tools are specficially designed to help businesses better understand their data, and can prove to be a huge benefit to those upgrading from what a limited spreadsheet can do.

What Is Business Intelligence?

Defining BI is tricky. When you examine what it does and why companies use it, it can start to sound vague and nebulous. After all, many different kinds of software offer analytics features, and all businesses want to improve. Understanding what a BI is or isn't can be unclear.

BI is an umbrella term meant to cover all of the activities necessary for a company to turn raw information into actionable knowledge. In other words, it's a company's efforts to understand what it knows and what it doesn't know of its own existence and operations. The ultimate goal is being able to increase profits and sharpen its competitive edge.

Framed that way, BI as a concept has been around as long as business. But that concept has evolved from early basics [like Accounts Payable (AP) and Accounts Receivable (AR) reports and customer contact and contract information] to much more sophisticated and nuanced information. This information ranges across everything from customer behaviors to IT infrastructure monitoring to even long-term fixed asset performance. Separately tracking such metrics is something most businesses can do regardless of the tools employed. Combining them, especially disparate results from metrics normally not associated with one another, into understandable and actionable information, well, that's the art of BI. The future of BI is already shaping up to simultaneously broaden the scope and variety of data used and to sharpen the micro-focus to ever finer, more granular levels.

BI software has been instrumental in this steady progression towards more in-depth knowledge about the business, competitors, customers, industry, market, and suppliers, to name just a few possible metric targets. But as businesses grow and their information stores balloon, the capturing, storing, and organizing of information becomes too large and complex to be entirely handled by mere humans. Early efforts to do these tasks via software, such as customer relationship management (CRM) and enterprise resource planning (ERP), led to the formation of "data silos" wherein data was trapped and useful only within the confines of certain operations or software buckets. This was the case unless IT took on the task of integrating various silos, typically through painstaking and highly manual processes.

While BI software still covers a variety of software applications used to analyze raw data, today it usually refers to analytics for data mining, analytical processing, querying, reporting, and especially visualizing. The main difference between today's BI software and Big Data analytics is mostly scale. BI software handles data sizes typical for most organizations, from small to large. Big Data analytics and apps handle data analysis for very large data sets, such as silos measured in petabytes (PBs).

Self-Service BI and Data Democratization

The BI tools that were popular half a decade or more ago required specialists, not just to use but also to interpret the resulting data and conclusions. That led to an often inconvenient and fallible filter between the people who really needed to get and understand the business—the company decision makers—and those who were gathering, processing, and interpreting that data—usually data analysts and database administrators. Because being a data specialist is a demanding job, many of these folks were less well-versed in the actual workings of the business whose data they were analyzing. That led to a focus on data the company didn't need, a misinterpretation of results, and often a series of "standard" reporting that analysts would run on a scheduled basis instead of more ad hoc intelligence gathering and interpretation, which can be highly valuable in fast-moving situations.

This problem has led to a growing new trend among new BI tools coming onto the market today: that of self-service BI and data democratization. The goal for much of today's BI software is to be available and usable by anyone in the organization. Instead of requesting reports or queries through the IT or database departments, executives and decision makers can create their own queries, reports, and data visualizations through self-service models, and connect to disparate data both within and outside the organization through prebuilt connectors. IT maintains overall control over who has access to which tools and data through these connectors and their management tool arsenal, but IT no longer acts as a bottleneck to every query and report request.

As a result, users can take advantage of this distributed BI model. Key tools and critical data have moved from a centralized and difficult-to-access architecture to a decentralized model that merely requires access credentials and familiarity with new BI software. This results in a whole new kind of analysis becoming available to the organization, namely, that of experienced, front-line business people who not only know what data they need but how they need to use it.

The emerging crop of BI tools all work hard at developing front-end tools that are more intuitive and easier to use than those of older generations—with varying degrees of success. However, that means a key criteria in any BI tool purchasing decision will be to evaluate who in the organization should access such tools and whether the tool is appropriately designed for that audience. Most BI vendors indicate they're looking for their tool suites to become as ubiquitous and easy to use for business users as typical business collaboration tools or productivity suites, such as Microsoft Office. None have gotten quite that far yet in my estimation, but some are closer than others. To that end, these BI tool suites tend to focus on three core types of analytics: descriptive (what did happen), prescriptive (what should happen now), and predictive (what will happen later).

What Is Data Visualization?

In the context of BI software, data visualization is a fast and effective method of transferring information from a machine to a human brain. The idea is to place digital information into a visual context so that the analytic output can be quickly ingested by humans, often at a glance. If this sounds like those pie and bar charts you've seen in Microsoft Excel, then you're right. Those are early examples of data visualizations.

But today's visualization forms are rapidly evolving from those traditional pie charts to the stylized, the artistic, and even the interactive. An interactive visualization comes with layered "drill downs," which means the viewer can interact with the visual to reach more granular information on one or more aspects incorporated in the bigger picture. For example, new values can be added that will change the visualization on the fly, or the visualization is actually built on rapidly changing data that can turn a static visual into an animation or a dashboard.

The best visualizations do not seek artistic awards but instead are designed with function in mind, usually the quick and intuitive transfer of information. In other words, the best visualizations are simple but powerful in clearly and directly delivering a message. High-end visuals may look impressive at first glance but, if your audience needs help to understand what's being conveyed, then they've ultimately failed.

Most BI software, including those reviewed here, comes with visualization capabilities. However, some products offer more options than others so, if advanced visuals are key to your BI process, then you'll want to closely examine these tools. There are also third-party and even free data visualization tools that can be used on top of your BI software for even more options.

Products and Testing

In this review roundup, I tested each product from the perspective of a business analyst. But I also kept in mind the viewpoint of users who might have no familiarity with data processing or analytics. I loaded and used the same data sets and posed the same queries, evaluating results and the processes involved.

My aim was to evaluate cloud versions alone, as I often do analysis on the fly or at least on a variety of machines, as do legions of other analysts. But, in some cases, it was necessary to evaluate a desktop version as well or instead of the cloud version. One example of this is Tableau Desktop, a favorite tool of Microsoft Excel users who simply have an affinity for the desktop tool (and who just move to the cloud long enough to share and collaborate).

I ended up testing the Microsoft Power BI desktop version, too, on a Microsoft representative's recommendation because, as the rep said, "the more robust data prep tools are there." Besides, said the rep, "most users prefer the desktop tool over a web tool anyway." Again, I don't doubt Microsoft's claim but that does seem weird to me. I've heard it said that desktop tools are preferred when the data is local as the process feels faster and easier. But seriously, how much data is truly local anymore? I suspect this odd desktop tool preference is a bit more personal than fact-based, but to each his own.

Then there's Google Analytics, a pure cloud player. The tool is designed to analyze website and mobile app data so it's a different critter in the BI app zoo. That being the case, I had to deviate from using my test data set and queries, and instead test it in its natural habitat of website data. Nonetheless, it's the processes that are evaluated in this review, not the data.

While I didn't test any of these tools from a data scientist's role, I did mention advanced capabilities when I found them, simply to let buyers know they exist. IBM Watson Analytics is one tool with the ability to extend to highly advanced features and was also one of the easiest to use upfront. IBM Watson Analytics is well-suited for business analysts and for widespread data democratization because it requires little, if any, knowledge of data science. Instead, it works well by using natural language and keywords to form queries, a characteristic that can make it valuable to practically anyone. It's highly intuitive, very powerful, and easy to learn. Microsoft Power BI is a strong second as it, too, is powerful while also familiar, certainly to any of the millions of Microsoft business users. However, there are several other powerful and intuitive apps in this lineup from which to choose; they all have their own pros and cons. We'll be adding even more in the coming months.

One thing to watch out for during your evaluations of these products is that many don't yet handle streaming data. For many users, that won't be a problem in the immediate future. However, for those involved with analyzing business processes as they happen, such as website performance metrics or customer behavior patterns, streaming data can be invaluable. Also, the Internet of Things (IoT) will drive this issue in the near future and make streaming data and streaming analytics a must-have feature. Many of these tools will have to up their game accordingly so, unless you want to jump ship in a year or two, it's best to think ahead when considering BI and the IoT.

BI and Big Data

Another area in which self-service BI is taking off is in analyzing Big Data. This is a newer development in the database space but it's driving tremendous growth and innovation. The name is an apt descriptor because Big Data generally refers to huge data sets that are simply too big to be managed or queried with traditional data science tools. What's created these behemoth data collections is the explosion of data-generating, tracking, monitoring, transaction, and social media tools (to name a few) that have become so popular over the last several years.

Not only do these tools generate loads of new data, they also often generate a new kind of data, namely "unstructured" data. Broadly speaking, this is simply data that hasn't been organized in a predefined way. Unlike more traditional, structured data, this kind of data is heavy on text (even free-form text) while also containing more easily defined data, such as dates or credit card numbers. Examples of apps that generate this kind of data include the customer behavior-tracking tools you use to see what your customers are doing on your e-commerce website, the piles of log and event files generated from some smart devices (such as alarms and smart sensors), and broad-swath social media tracking tools.

Organizations deploying these tools are being challenged not only by a sudden deluge of unstructured data that quickly strains storage resources [think beyond terabytes (TB) into the PB and even exabyte (EB) range] but, even more importantly, they're finding it difficult to query this new information at all. Traditional data warehouse tools generally weren't designed to either manage or query unstructured data. New data storage innovations such as data lakes are emerging to solve for this need, but organizations still relying exclusively on traditional tools while deploying front-line apps that generate unstructured data often find themselves sitting on mountains of data they don't know how to leverage.

Enter Big Data analysis standards. The golden standard here is Hadoop, which is an open-source software framework that Apache specifically designed to query large data sets stored in a distributed fashion (meaning, in your data center, the cloud, or both). Not only does Hadoop let you query Big Data, it lets you simultaneously query both unstructured as well as traditional structured data. In other words, if you want to query all of your business data for maximum insight, then Hadoop is what you need.

You can download and implement Hadoop itself to perform your queries, but it's typically easier and more effective to use commercial querying tools that employ Hadoop as the foundation of more intuitive and full-featured analysis packages. Notably, most of the tools reviewed here, including Chartio, IBM Watson Analytics, Microsoft Power BI, and Tableau Desktop, all support this. However, each requires varying levels of configuration or even add-on tools to do so—with IBM, Microsoft, and Tableau offering exceptionally deep capabilities. However, both IBM and Microsoft will still expect customers to utilize additional tools around aspects such as data governance to ensure optimal performance.

Finding the Right BI Tool

Given the issues spreadsheets can have when used as ad hoc BI tools and how firmly ingrained they are in our psyches, finding the right BI tool isn't a simple process. Unlike spreadsheets, BI tools have major differences when it comes to how they consume data inputs and outputs and manipulate their tables. Some tools are better at exploration than analysis, and some require a fairly steep learning curve to really make use of their features. Finally, to make matters worse, there are dozens if not hundreds of such tools on the market today, with many vendors willing to claim the self-serve BI label even if it doesn't quite fit.

Getting the overall workflow down with these tools will take some study and discussion with the people you'll be designating as users. Tableau Desktop and Microsoft Power BI, for example, will start users out with the desktop version to build visualizations and link up to various data sources. Once you have this together, you can start sharing those results online or across your organization's network. With others, such as Chartio or Google Analytics, you start in the cloud and stay there.

In recent years, companies have been taking advantage of the wide selection of online learning platforms out there to train their employees on using these platforms. As intuitive as these platforms may be, it is important to make sure that your employees actually know how to use these BI platforms so that you can make sure your investment was worthwhile. There are many ways of approaching this, but using the right online learning platform might be a good place to start looking.

Given the wide price range of these products, you should segment your analytics needs before you make any buying decision. If you want to start out slowly and inexpensively, then the best route is to try something that offers significant functionality for free, such as Microsoft Power BI. Such tools are very affordable and make it easy to get started. Plus, they tend to have large ecosystems of add-ons and partners that can be a cost-effective replacement for doing BI inside a spreadsheet. Tableau Desktop still has the largest collection of charts and visualizations and the biggest partner network, though both IBM Watson Analytics and Microsoft Power BI are catching up fast.

IBM Watson Analytics scored the highest, and Microsoft Power BI and Tableau Desktop scored the next highest in our roundup. However, all three products received our Editors' Choice award. Tableau Desktop may have a big price tag depending on which version you choose but, as previously mentioned, it has an exceptionally large and growing collection of visualizations plus a manageable learning curve if you're willing to devote some effort to it. Microsoft Power BI and Tableau Desktop also have large and growing collections of data connectors, and both Microsoft and Tableau have their own sizable communities of users that are vocal about their wants and needs. This can carry a lot of weight with the vendors' development teams so it's a good idea to spend some time looking through those community forums to get an idea where these companies are headed.

  • Pros: Extremely user-friendly. Fantastic automatic report generation. Impressive support availability.

    Cons: Automated reports can quickly become defaults. Steep learning curve that might confuse beginners.

    Bottom Line: Zoho Reports is a solid option for general business users who might not be knowledgeable in analytics software. It's also available at an attractive price.

    Read Review
  • Pros: Accessible user interface. Smart guidance features. Impressively fast analytics. Robust natural language querying.

    Cons: Unable to do real-time streaming analytics.

    Bottom Line: IBM Watson Analytics is an exceptional business intelligence (BI) app that offers a strong analytics engine along with an excellent natural language querying tool. This is one of the best BI platforms you'll find and easily takes our Editors' Choice honor.

    Read Review
  • Pros: Extremely powerful platform with a wealth of data source connectors. Very user-friendly. Exceptional data visualization capabilities.

    Cons: Desktop and web versions divide data prep tools. Refresh cycle is limited on free version.

    Bottom Line: Microsoft Power BI earns our Editors' Choice honor for its impressive usability, top-notch data visualization capabilities, and superior compatibility with other Microsoft Office products.

    Read Review
  • Pros: Enormous collection of data connectors and visualizations. User-friendly design. Impressive processing engine. Mature product with a large community of users.

    Cons: Full mastery of the platform will require substantial training.

    Bottom Line: Tableau Desktop is one of the most mature offerings on the market and that shows in its feature set. While it has a steeper learning curve than other platforms, it's easily one of the best tools in the space.

    Read Review
  • Pros: Bottlenecks are eliminated thanks to in-chip processing. Impressive natural language query in third-party applications.

    Cons: Might be too difficult for self-service business intelligence (BI). Analytics process still needs to be ironed out. Natural language capability can be limited.

    Bottom Line: Sisense is a complete platform that should be popular for experienced BI users. It may fall short for beginners, however.

    Read Review
  • Pros: Wide range of connectors. Impressive sharing features. Limitless data storage.

    Cons: User interface is not intuitive. Steep learning curve. Unwelcoming to new analysts.

    Bottom Line: Domo isn't for newcomers but for companies that already have business intelligence (BI) experience in their organization. Domo's a powerful BI tool with a lot of data connectors and solid data visualization capabilities.

    Read Review
  • Pros: Exceptional platform for website and mobile app analytics.

    Cons: Customer support has way too much automation. Focus on marketing and advertising can be frustrating to users. Relies mostly on third parties for training.

    Bottom Line: Due to its brand recognition and the fact that it's free, Google Analytics is the biggest name in website and mobile app intelligence. It has a steep learning curve but it is an awesome business intelligence tool.

    Read Review
  • Pros: Designed with general business users in mind. Solid return on investment.

    Cons: The data you can use is limited. Needs additional platform to connect.

    Bottom Line: The Salesforce Einstein Analytics Platform is designed for customer, sales, and marketing analyses, although it can server other needs, too. Its powerful analytics capabilities along with its solid natural language querying functionality and a wide array of partners make it an attractive offering.

    Read Review
  • Pros: Real-time analytics for Internet of Things (IoT) and streaming data features. Massive ecosystem with plentiful extenders. Responsive pages make mobile publishing easiest. Impressive storytelling paradigm. Centralized view with consolidated analytics.

    Cons: Data prep features are lacking. Confusing toolbar design. Not friendly for beginners.

    Bottom Line: If your business already uses SAP's HANA database platform or some of its other back-end business platforms, then SAP Analytics Cloud is a powerful, well-priced choice. But be warned that there's a steep learning curve and a noted dependence on other SAP products for full functionality.

    Read Review
  • Pros: Impressive processing engine. Powerful query optimization on SQL. Entirely web-based. Complex queries are handled very well.

    Cons: Poorly designed user interface. Steep learning curve.

    Bottom Line: Chartio excels at building a powerful analytics platform that experienced business intelligence (BI) users will appreciate. Those new to BI, however, will find it very difficult to use.

    Read Review
  • Pros: Very deep SQL modeling ability. Uses Git for version management and collaboration.

    Cons: Very expensive. Not for small teams.

    Bottom Line: Looker is a great self-service business intelligence (BI) tool that can help unify SQL and Big Data management across your enterprise.

    Read Review
  • Pros: Custom access roles. Solid collection of public data online.

    Cons: Complex pricing is a deterrent.

    Bottom Line: Qlik Sense Enterprise Server is a self-service business intelligence (BI) tool that delivers the best collection of user access roles among the BI tools we tested, and also demonstrates a promising start towards integrating Data-as-a-Service (DaaS).

    Read Review
  • Pros: One of the largest collections of data connectors. Many granular access roles.

    Cons: No free trial available. Training webinars can be costly.

    Bottom Line: The company's Focus query language is showing its age but Information Builders' self-service business intelligence (BI) tool WebFocus nevertheless has some powerful analysis features.

    Read Review
  • Pros: Very easy to get started. Nice team management and collaboration features.

    Cons: The cloud version has a subset of features found in Windows version. Online documentation could be improved.

    Bottom Line: While Tibco is still making the transition from a desktop to a cloud software vendor, its self-service business intelligence (BI) tool Tibco Spotfire is a great way to start visualizing your Excel data.

    Read Review
  • Pros: Excellent analytical support for Intuit QuickBooks. Very easy setup.

    Cons: Installation and setup is a bit of chore. No support for Intuit QuickBooks' online versions.

    Bottom Line: Clearify QQube is the best self-service business intelligence (BI) tool for in-depth analysis of your Intuit QuickBooks files, though you'll need to look elsewhere for broader BI tasks.

    Read Review

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    REDMOND, Wash., Sept. 16, 2014 /PRNewswire/ -- Microsoft Corp. on Tuesday announced that Teri List-Stoll, executive vice president and chief financial officer of Kraft Foods Group Inc., and Charles W. Scharf, chief executive officer of Visa Inc., have been appointed to the company's board of directors and will join the board effective Oct. 1, 2014.

    The company also announced that Dave Marquardt and Dina Dublon have decided not to seek reelection to the board of directors and will retire from the board at the expiration of their current term following the annual shareholders meeting in December.

    Microsoft also announced its board of directors declared a quarterly dividend of $0.31 per share, reflecting a 3-cent, or 11 percent, increase over the previous quarter's dividend. The dividend is payable Dec. 11, 2014, to shareholders of record on Nov. 20, 2014. The ex-dividend date will be Nov. 18, 2014.

    "As we continue to focus on the company's transformation and the board continues to evaluate capital strategy options, this dividend increase is another step in our ongoing commitment to increase capital returns to shareholders," said Amy Hood, chief financial officer of Microsoft.

    Scharf, 49, has served as CEO of Visa since November 2012. Before joining Visa, Scharf spent nine years at JPMorgan Chase & Co. as the chief executive officer of Retail Financial Services and managing director at One Equity Partners, the firm's private investment arm. He has also served as the chief executive officer and chief financial officer of Bank One Corp., and chief financial officer of both Salomon Smith Barney and the global corporate and investment bank division of Citigroup Inc. He serves on the board of trustees for Johns Hopkins University and the board of directors for the Financial Services Roundtable.

    List-Stoll, 51, is executive vice president and chief financial officer for Kraft Foods Group, Inc. Before joining Kraft, she served as senior vice president and treasurer at Procter & Gamble. Previously, over the course of a nearly 20-year career at Proctor & Gamble, she held finance leadership roles across a diverse range of areas including business unit management, supply chain, sales, accounting, and financial planning and analysis. She serves on the board of Danaher Corp. and as a trustee of the Financial Accounting Foundation.

    "These additions help strengthen our ability to serve our shareholders and work with Satya and the company's senior leadership team on Microsoft's ongoing transformation," said John Thompson, Microsoft chairman.

    "I'm excited to have both Teri and Charlie joining our board," said Satya Nadella, CEO of Microsoft. "Teri brings exceptional financial and operational expertise, as well as great insights from her two decades of experience in consumer and retail industries. Charlie, as a sitting CEO of a large global business, brings additional strategic and operational depth to the Microsoft board, as well as a deep understanding of how commerce is changing globally." 

    Marquardt, 65, has served on the Microsoft board since 1981 in a variety of capacities. Dublon, 61, joined the Microsoft board in 2005, and has chaired the compensation committee.

    "As one of our earliest board members, Dave has played an indispensable role in Microsoft's growth and development, providing sage counsel and invaluable industry insights," said Bill Gates, founder and technology advisor of Microsoft. "Dina has also been a great board member for almost a decade, and we all appreciate her guidance and support."

    Adding List-Stoll and Scharf will increase Microsoft's board to 12 members effective Oct. 1.

    Scharf will be joining the board's governance and nominating committee. List-Stoll will be joining the audit committee.

    In addition to List-Stoll and Scharf, Microsoft's board of directors consists of John W. Thompson, Microsoft chairman and chief executive officer of Virtual Instruments; Dina Dublon, former chief financial officer of JPMorgan Chase; Bill Gates, Microsoft founder and technology advisor; Maria M. Klawe, president, Harvey Mudd College; David F. Marquardt, general partner at August Capital; G. Mason Morfit, president, ValueAct Capital; Satya Nadella, Microsoft CEO; Charles H. Noski, former vice chairman of Bank of America Corp.; Dr. Helmut Panke, former chairman of the board of management at BMW AG; and John W. Stanton, chairman, Trilogy Equity Partners and Trilogy International Partners.

    Founded in 1975, Microsoft (Nasdaq: MSFT) is the worldwide leader in software, services, devices and solutions that help people and businesses realize their full potential.

    Logo - http://photos.prnewswire.com/prnh/20000822/MSFTLOGO

    SOURCE Microsoft Corp.


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