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    An enterprise guide to big data in cloud computing Share this item with your network: Business intelligence BI is a technology-driven process for analyzing data and presenting actionable information to help executives, managers and other corporate end users make informed business decisions.

    Download this free guide Staff Pick: The Rising Need for Analytics Accuracy Learn how LinkedIn overcame analytics bottlenecks, 3 data modeling flaws that cripple data science projects, and common roadblocks of advancing data science teams and hiring data pros. Start Download You forgot to provide an Email Address.

    This email address is already registered. You have exceeded the maximum character limit. Please provide a Corporate E-mail Address. Please check the box if you want to proceed. I agree to my information being processed by TechTarget and its Partners to contact me via phone, email, or other means regarding information relevant to my professional interests.

    I may unsubscribe at any time. BI encompasses bi dating site advice wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources; prepare it for analysis; develop and run queries against that data; and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers.

    What came to be known as BI tools evolved from earlier, often mainframe-based analytical systems, such as decision support systems and executive information systems.

    Comparison of BI and bi dating site advice analytics Business intelligence is sometimes used interchangeably with business analytics ; in other cases, business analytics is used either more narrowly to refer to advanced data analytics or more broadly to include both BI and advanced analytics.

    Why is business intelligence important? The potential benefits of business intelligence tools include accelerating and improving decision-making, optimizing internal business processes, increasing operational efficiency, driving new revenues and gaining competitive advantage over business rivals.

    BI systems can also help companies identify market trends and spot business problems that need to be addressed.

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    BI data can include historical information stored in a data warehouseas well as new data gathered from source systems as it is generated, enabling BI tools to support both strategic and tactical decision-making processes. Initially, BI tools were primarily used by data analysts and other IT professionals who ran analyses and produced reports with query results for business users. Increasingly, however, business executives and workers are using BI platforms themselves, thanks partly to the development of self-service BI and data discovery tools and dashboards.

    BI technology also includes data visualization software for designing charts and other infographics, as well as tools for building BI dashboards and performance scorecards that display visualized data on business metrics and key performance indicators in an easy-to-grasp way. Data visualization tools have become the standard of modern BI in recent years.


    A couple leading vendors defined the technology early on, but more traditional BI vendors have followed in their path. Now, virtually every major BI tool incorporates features of visual data discovery. BI programs may also incorporate forms of advanced analytics, such as data mining, predictive analyticstext mining, statistical analysis and big data analytics. In many cases, though, advanced analytics projects are conducted and managed by separate teams of data scientistsstatisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.

    Business intelligence data is typically stored in a data warehouse or in smaller data marts that hold subsets of a company's information. In addition, Hadoop systems are increasingly being used within BI architectures as repositories or landing pads for BI and analytics data -- especially for unstructured data, log files, sensor data and other types of big data. Before it's used in BI applications, raw data from different source systems must be integrated, consolidated and cleansed using data integration and data quality tools to ensure that users are analyzing accurate and consistent information.

    BI trends In addition to BI managers, business intelligence teams generally include a mix of BI architects, BI developers, business analysts and data management professionals. Business users are also often included to represent the business side and make sure its needs are met in the BI development process. To help with that, a growing number of organizations are replacing traditional waterfall development with Agile BI and data warehousing approaches that use Agile software development techniques to break up BI projects into small chunks and deliver new functionality to business analysts on an incremental and iterative basis.

    Doing so can enable companies to put BI features into use more quickly and to refine or modify development plans as business needs change or as new requirements emerge and take priority over earlier ones. BI for big data BI platforms are increasingly being used as front-end interfaces for big data systems. Modern BI software typically offers flexible back ends, enabling them to connect to a range bi dating site advice data sources. This, along with simple user interfaces, makes the tools a good fit for big data architectures.

    Users can connect to a range of data sources, including Hadoop systems, NoSQL databasescloud platforms and more conventional data warehouses, and can develop a unified view of their diverse data.


    Because the tools are typically fairly simple, using BI as a big data front end enables a broad number of potential users to get involved rather than the typical approach of highly specialized data architects being the only ones with visibility into data. This was last updated in August Next Steps Learn how business intelligence and analytics tools can benefit corporate strategies and operations, and what you should know before buying them.

    Continue Reading About business intelligence BI.
    This category includes BI tools for ad hoc data analysis. This is either a one-time analysis or the formulation of a recurring analysis that users share. Users have dual roles as information consumers and analytics producers when they share or publish a BI application created with a self-service BI tool. Users typically have the word analyst in their title -- e. Management staff may also use these tools when doing business analyst -- or analytical guru -- work for their managers or peers, even if their titles don't imply that.

    Whereas guided discovery tools operate with a preset collection of data and metrics, self-service BI bi dating site advice enable business bi dating site advice to add data and define new metrics when performing analysis without IT intervention. However, there are some considerations to the no IT involvement needed hype pitched by some BI vendors. First, IT manages data source access based on need, security and privacy rights, so business users performing analyses must obtain the proper privileges to add data sources.

    Second, the data sources must be consumable by the BI tool. Although business intelligence software can easily access most data sources, specific sources may prohibit access. Third, the data source must be understandable by the business user, which often requires business people working with IT to get an explanation of the data schema and definitions the business people need to analyze.

    Finally, no matter how easy the business people perceive the BI tool to be, IT must train and support the business in its effective use, both to improve business users' productivity and to increase the return on investment of these tools. The BI tool styles in this category include: Ad hoc reporting and analysis Online analytical processing -- also referred to as OLAP cubes Data discovery Data visualization Advanced BI and analytics encompasses the tools data scientists use to create predictive and prescriptive analytical models.

    This includes predictive analytics, statistical modeling, data mining and big data analytics software. Here, data scientists tend to spend a great deal of time ingesting, integrating and cleansing data. This category is outside the scope of this article, but it is mentioned here in order to provide the entire spectrum of BI tool styles.

    Here's a look at other BI tool categories and styles: Business intelligence software types and features How to buy BI analytics tools Each of the BI styles discussed here originated as stand-alone, specialized BI tools sold by emerging BI vendors.

    As enterprises experienced the benefits of BI tools and recognized their value, the following occurred: A key buying question an enterprise must ask is: Is it better to buy a BI suite from one BI vendor or to purchase separate products from multiple vendors?

    Although other articles in this series deal with this question in depth, consider some key concepts. First, buy what's needed and don't just acquire the BI product with the most features. The enterprise may not need all that's offered.

    Business need and best fit should guide the selection process for the maximum benefit of BI tools. Second, an enterprise needs to examine the costs and skills necessary to develop and manage BI applications, not just the purchase or subscription cost.

    Sometimes, BI suites are more cost- and resource-effective than stand-alone BI tools. However, other times, they're much more complex, resulting in higher costs, longer development lead times and the need for a greater pool of skills. Who buys BI analytics tools? BI and analytics tools investment and use offer long-term growth, regardless of the economic cycle.

    It has accelerated in recent years as enterprises have learned the benefits of BI tools, and they are now craving real-time data to not just grow and improve, but also to manage their businesses on a daily basis. Historically, BI has been the domain of large enterprises due to the complexity, costs and skills required -- but during the past several years, those factors have changed dramatically, resulting in small and medium-sized businesses SMBs becoming significant BI buyers.

    Many enterprises, regardless of size, initially leverage the reporting capabilities offered by their business application vendors -- such as SAP, Oracle, Microsoft, Infor and Epicor -- and use spreadsheets to fill in the gaps, especially when their focus is on tactical operational reporting. But this approach often results in data silos, limiting the ability of an enterprise to utilize the effects of its BI efforts and experience the benefits of BI tools to grow revenue and operate more effectively.

    In addition, this approach wastes people's time comparing and reconciling data from these silos -- time that could be better spent running the business. When the limitations and costs of this approach become apparent, the enterprise can institute BI technology that's independent of their operational applications. In the early days, only industries with the most significant need for data used BI. Today, enterprises in all industries have information-intensive processes that require the benefits of BI tools.

    The scale of the information enterprise's need to analyze varies by industry and company size, and it can impact which specific BI tools companies should consider. However, that shouldn't impact the particular BI categories and styles needed. In addition, the BI market is rife with merger and acquisition activity, so even people in the industry are sometimes confused as to who owns what.

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    BI vendors can be split into three groups. These companies secured their top positions by acquiring the market leaders about eight years ago -- Cognos, Business Objects and Established BI specialists. These vendors offer the latest wave of BI innovation, such as data discovery, data visualization and cloud BI. Although many consider Microsoft a tech titan in BI software, the company previously wasn't a recognized leader; however, in the past few years, it has emerged as a significant player, particularly in the SMB market, which is now embracing the benefits of BI tools.

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    How will business people access the BI software -- on the front end? Where will the BI application itself operate -- on the back end? Although there are some BI and analytics tools that exclusively use desktop client applications, almost all offer a browser-based client interface that works across all the major web browsers.

    BI vendors were slow to implement native-based bi dating site advice interfaces and instead relied on tablet and smartphone browsers; however, with the expanded use of mobile devices for businessthat's changing. Although most users deploy BI application servers on premises in an enterprise's data center, companies are deploying more applications on private clouds hosted by companies such as Amazon, IBM and Rackspace.

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    When the BI client interface is browser-based, companies can make the decision to deploy the BI tool on premises or in the cloud based on their data center strategy rather than by the limitations of the BI tool. There are emerging BI players that exclusively provide cloud-based BI deploymentsoften in a multi-tenant SaaS environment, with the cloud BI vendor ensuring security and privacy.

    With a better understanding bi dating site advice the different tool categories, the vendor landscape and how BI analytics tools are deployed, the next step is to determine how your company can best utilize the benefits of BI tools. First, the enterprise must identify its needs and take a closer look at some typical use cases for which these tools are optimized. This was last published in April Related Resources.
    Enjoy this article as well as all of our content, including E-Guides, news, tips and more.

    Step 2 of 2: You forgot to provide an Email Address. This email address is already registered. Bi dating site advice have exceeded the maximum character limit. Please provide a Corporate E-mail Address. Please check the box if you want to proceed. I agree to my information being processed by TechTarget and its Partners to contact me via phone, email, or other means regarding information relevant to my professional interests.

    I may unsubscribe at any time. Until quite recently, an organization that wanted to analyze data stored within a SharePoint team site had to upload that data to Power BI. Doing so could be problematic when it came to large data files, and it raised questions about the potential for data exposure.

    The process is even easier by allowing linking to a SharePoint team site without requiring the Pro version of Power BI. The Get Data screen allows you to select the data source that you want to use. As shown in figure one, none of the data sources specifically mention SharePoint.

    The reason for this is that Power BI doesn't really analyze SharePoint data, but rather Excel spreadsheet data that is stored within a SharePoint document library. Clicking on the Get button located within the Files section will connect you to a SharePoint team site. Power BI then asks you to specify the location of the file data needed.

    Microsoft has taken steps to streamline the process. If you don't know the URL, simply clicking the Connect button will bring up any root level content that Power BI is able to locate, as shown in figure three. If you simply click Connect without entering anything, Power BI will display all the document libraries that it can find. This process works well for document libraries in SharePoint Online.

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    If, however, you use an on-premises SharePoint deployment, then there is a good chance a URL is necessary as a way of helping Power BI locate your document libraries. It may also be helpful to go ahead and enter a URL if you have a large collection of team sites. At this point, you can click on your document library, select the file that you want to analyze as shown in figure four, and then click Connect.

    Select the file that you want to analyze and click Connect. You can choose to import the data or connect to the data. Importing the data causes Power BI to connect to the document within the SharePoint document library. This allows you to create Power BI reports and dashboards; the data is automatically refreshed directly from SharePoint. The alternative is to import the Excel workbook into Power BI. This approach will let you use Excel-level elements such as charts and pivot tables directly within Power BI, but will create two separate copies of the spreadsheet.

    If you need to keep the spreadsheet data up-to-date, you will have to use a scheduled refresh. In most cases, it is better to use the Refresh option unless you bi dating site advice a compelling reason to import a full-blown spreadsheet.

    Figure five shows a spreadsheet within Power BI. This is what it looks like when you import an entire Excel workbook into Power BI. Although it is preferable to import data rather than import an entire spreadsheet, the import function will work only if the spreadsheet is properly formatted.

    Otherwise, you will receive an error indicating that Power BI cannot locate any data within the Excel workbook. Power BI requires that the first row of any imported spreadsheet contain column headers. You will notice in the previous figure that my spreadsheet has column headers. Although the header text exists, the text has not been designated as such. You have to format the data as a table for Power BI to recognize it.

    The exact method of doing this varies depending on the version of Excel that you are using. In Excel you can simply select your data, including the headers; click the Table button found on Excel's Insert tab; and select the My Table Has Headers check box that is displayed within the resulting dialog box. Microsoft provides a full set of instructions here.

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