Information Technology Management And Business Intelligence: Functions, Features And Applications

Executive dashboards

Information technology management is the method where every resource regarding information technology has been managed. This is done as per the needs and priorities of the business. Here, this comprises tangible resources such as computers and individuals, networking hardware and real resources such as data and software.

On the other hand, business intelligence refers to analysis, budgeting, presentation, accumulation of business data. Here the aim is to develop visibility of economic status and organisational operations for managing a business.

In this report, a detailed explanation of functions and features and ways to align towards the functional operational and areas are discussed. Next, how the information system has been assisting the business in developing business operations are analysed. Lastly, how his information system has been helping project managers to manage projects are demonstrated.

Irrespective of clear agenda, various elements insist upon on BI solution. This is regardless of the situations of their application:

Executive dashboards Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Personalized dashboards have been providing practical and relevant real-time to business leaders. This has been enabling better and faster decision-making through lowering reaction times to external and internal events. Here, the executives have required access to various personalised dashboards for supplying easy-to-understand summary information and KPIs on a scheduled and regular basis (Bukhari and Kazi 2016). Moreover, exception reporting has been alerthat the executive and unexpected scenarios and events need that action.
Location intelligence	It is a capability of visualizing and mapping data under different geographical formats. The exploration and imagining of various data sets are lying from spatial elements (Moro, Cortez and Rita 2015). These have been enabling organizations to know business operations from latest view-points.
What-if analysis	This helps business to analyze the potential impacts of different kinds of business decisions prior they are made (Fan,  Lau and Zhao 2015).
Interactive reports	This is helpful for users to convert data into knowledge. Here, they have been allowing to understand the analysis under description better and underpinning data where statements have been based on for supporting better decision making.
Metadata layer	This has been making the reporting easier and eradicating the necessities to cod. This is helpful for users and writers to fetch data in easy terms of business (Kisielnicki and Misiak 2016). Here, the users have been solely interacting with information at the level of data. This is done instead of any need to comprehend complicacies of underpinning database or data.
Ranking reports	It helps in creating reports ordering particular categories of data from various dimensions. This is done by selecting specific criteria. These ranking reports have been helpful to see the most effective and also worst performing elements of a business. Here, for instance, one can create reports tanking to be the top-selling products, salespeople or regions (Forsgren and Sabherwal 2015).

Business intelligence tools has comprised of some everyday tasks. However, the primary purpose has been supporting of the decision-making process of a company. This is helpful for knowledge workers like research analysts and managers to make quicker and better decisions. Various functions of business intelligence technologies have been varying as per industry standards. Here, for instance, these can be utilized for manufacturing to perform customer support and shipment. This can also be done in retail for user profiling and targeting, in banking and economic services regarding risk analysis and claims to transportation for making fleet management (Sangar et al. 2015). This is applied in telecommunication be aware of rates of customer drop-offs, utilities and power for analyzing power usage. Here, the entire business intelligence includes a process of data analysis to boost the performance of a company concerning their competitors through helping different end users under the organization and undertake much effective informed decisions.

This technology-driven procedures of business intelligence have involved different functions, tools of technologies, methodologies and applications. This helps organizations to collect data and then prepare investigations. The database queries are conducted and developed and after that reports are generated. Here, all types of functions are helpful for supporting decisions of the business. Here, data used under business intelligence has been including previous and latest data that are collected from external sources (Fan, Lau and Zhao 2015). Next, business intelligence took that information and assimilated a comprehensive set of applications and functions like performance scorecards, dashboards, data visualization software, online analytical processing, enterprise reporting, querying and ad hoc analysis. Thus it is seen that applications of business intelligence applications having distinct and vital functions are bought separately from different vendors of the third party and as an element of a platform of single business intelligence (Williams 2014).  

Here, the most ubiquitous and most straightforward path, interestingly driven by minimum real value is reporting. This reveals what has been already happening. Here, one of the primary aspects is to be highly static. Here, the following function values ladder and complexity which is also known as analysis. Since a study has been focusing on what has been happening. This has been more costly to contribute to making effective decisions (Moro, Cortez and Rita 2015). Next, monitoring has been taking people to the next level of complexity. This is to show precisely what has been happening at that point. This has provided immense value through permitting for identifying issues, correct and intervene the near real time. This is instead of waiting for any report to reveal how weak the tasks are done and assuring post-mortem to inform how the poor outcomes have taken place. Lastly, the holy grail of BI has been predictive analytics. This processes information to come up with various predictions of what has been happening for future (Kisielnicki and Misiak 2016). As this has not been widespread under multi-family housing, different predictive analysis has been there already for stacking common technology. Here, applications of credit scoring have predicted distressed debt and pricing. Further, revenue management systems have been optimally predicting rents for balancing yields and occupancies.

Location intelligence

The above duties and features are beneficial to gain various insights to create timely and accurate business decisions. At any time, executives have been making decisions from best guess and gut feeling. Here, the choices are made inaccurate as they are not informed. Business intelligence has been using decisions that are insight-driven and data with gut feeling (Sauter 2014). This is a help to assess data in real-time to make immediate decisions. Further, new revenues opportunities are identified here. They are also able to determine the data. One can obtain various insights regarding useful scope that the business has missed in the past. Next, the new revenue opportunities are also identifiable. Through assessing all data, one can retrieve insights regarding current scopes that one have missed in the past (Larson and Chang 2016). One can develop or adjust for current market situations for satisfying customers. Further, the KPIs can be tracked successfully through receiving notifications and alerts all the time the data has been changing about particular KPI. As the data has been improving, one can get notified and has been able to drill down what has happened and what can be done to fix that.

Moreover, the functions and features have been allowing various kinds of users in accessing dashboards and data. Having different solutions for self-service, users of business has not been needed to rely entirely on IT and access data and generate dashboards. Besides, one can also get access to initial reports and metrics. As one uses BI tools that are governed through self-service, it helps users to gain benefit from business intelligence. However, only one version of the truth is maintained here (Sauter 2014). Moreover, it is also helpful to have an overall overview of customers. One can know customer behavior more efficiently and use that to supply customers with various customized offers. Understanding what customers have been buying or not at any time for a place, is helpful to change the data to benefit.

Besides, it is useful for better inventory management. This is helpful to control inventory amounts orders and logistics for proper management. It is also beneficial to find out anomalies within inventory data. Next, efficiencies can also be improved in this case. The BI solutions have been saving substantial time by providing insights very fast. The functions are also helpful for more exact allocation of resources. The elements are beneficial to know what areas of business have required more resources (Peters et al. 2016). Moreover, business intelligence is useful to analyze precisely how all units of activity has been performing and providing insights regarding how to develop that. Ultimately, they are also helpful to take advantages of the potential of the team. This is done through collaborating and creating discussions with various team members as they fund ant change in data. This is also helpful to make more effective decisions. These are also helpful to seek relevant individuals for particular challenges and develop an ad-hoc team to solve that (Wu, Chen and Olson 2014).

What-if analysis

Business intelligence denotes the way in which computer software with various other tools. Thus they have been collecting every kind of complicated business information. This is for condensing that to reports. Here, the data collected has been focusing on a particular department and provide a complete view of the overall status of the company (Stone and Woodcock 2014). Huge corporations have been possessing a high quantity of data for processing that to benefit notably from business intelligence. This is done through the same type of concerns that are used.

Business intelligence may help a company identify its most profitable customers, trouble spots within its organization, or its return on investment for specific products. Although a companywide business intelligence system is complex, costly and time-consuming to establish, when implemented and used correctly, its benefits can be significant (Camilleri 2016).

First of all fact-based decisions can be taken. As the system of company-wide business intelligence is appropriately placed, the management can fetch current and detailed data on every aspect of a business. This includes customer, production data and economic data (Schulz, Winter and Choi 2015). Here, the reports can be read and the information can be synthesized in various types of pre-determined methods. Thus an immediate return on investment reports of distinct product line and products can be done. Here, the information has been helpful for management to develop various fact-based decisions. This includes products for concentrating on and one that has been discontinuing. It is also beneficial for developing negotiations and sales. These are also essential resources for a company’s sales force because it provides access to reports that have even identified trends and sales, additions and improvements of products, present preferences of customers and various unexplored markets.

Here, current and detailed data are also crucial for backing up negotiations along with vendors and suppliers (George, Schmitz and Storey 2018). Moreover, it has been eliminating wastes where business intelligence systems have been pointing out areas of waste and loss that have been unnoticed previously in huge organizations. As companywide BI system has been working as a single, with a unified whole, it can analyze transactions taking place between departments and subsidiaries for identifying sectors of inefficiency and overlapping. Next, it is also helpful to determine various scopes. This is done by analyzing individual abilities, comparing relative strengths and weaknesses against the competitors (Baur et al. 2014). Next, the market conditions and trends are also identified and they must react very fast to those changes. This is to gain competitive advantages and helping decision makers for acting swiftly and adequately to respond to scopes. This is also helpful for organizations to determine most customers who are profitable. This also increases various profitable customers potentially. This is to analyze the causes for the dissatisfaction of customers prior it starts to cost those sales.

Regarding actionable intelligence significant cause to gain BI is to ground their ability for providing various actionable information. This has been highly vital to provide business user tools and providing simple and easy access to data and legacy database and mounts of latest data from geolocation (Foshay and Kuziemsky 2014). Moreover, there is information integration. Here the data has been tending to speed around and trapped under different silos. Here, the current wave of tools of BI is to eradicate restrictions taking place between those silos. Hence a holistic image is formed from various kinds of sources of data. This to suggest more accurate forecasts. The companies have been thinking according to data alters that are connected every time. For instance, Hortonworks Connected Data platforms are integrated with the tools of business intelligence such that business analysts can access trillions of data objects (Vossen 2014). This is done directly from favourite business intelligence deployments instead of any necessity of movement of data. Then there is sales personalization. This contribution made by a business intelligence has been making the entire success of the enterprise that can never be overstated in current economic standards of the digital world.

Interactive reports

Next, targeted and personalized online experience of business has delivered to customers is one of the causes with the cost of savings. The online retailers with average sales for every employee with well-known companies have never possessed digital string presence. Traditional platforms of BI has been coming a long way with the previous decade (Wieder and Ossimitz 2015). At last, they have been using glean intelligence taking place from the smaller subset of data. These have been overseen by various specialists who were the only people who have been able to interpret and access that data. Here, businesses have been able to ask questions and specialist has been getting back them some days with reaction. However, business analytics and intelligence that are used currently have been the legacy of BI of GUIs with RDBMS data warehouse. This has also involved involvement of human analyst. Apart from this, this is machine-initiated and including assimilation of transactional interactions over the Internet having analytics and searching operations. This happens at machine speed which is lightning fast. Here, this kinds of BI has been denoted as an HTAP or “Hybrid Transaction Analytical processing”.

This has been enabling a business to customize effectively to the online experience of customers with interactions. This has been positively influencing the process to buy and helping them in winning over those competitors who have not been using that current BI method (Popovi? et al. 2014). Moreover, there has been the real-time making of decisions. At previous days, the data warehouses have been utilized for aggregating information from various business lines and departments. BI tools have also been providing a unified perspective of operations for managers for recognizing scopes for efficiencies and growths. However, this kind of approach has been losing the platform of systems making executive decisions in real-time on the ground of present data.

Instead of static analysis of previous operations, however current platforms of big data has been bringing various analytical abilities, as per as operational data for making decisions whenever business takes place. This is the expectation of pushing previous conventional intelligence and capabilities of reporting driving the downfall of legacy data technologies of warehousing. These are being seen in the current market (Sallam et al. 2014). However, at ending the insights are created and the ability to act on those insights in actual time has been bringing real time higher than the business value. Next, there is an everyman analysis. Since consumers have been consuming orders of magnitude with more as compared to prior generations.

This uprising of the search engine and a smartphone made on the information accessible to any person on a daily basis. These latest technologies of business intelligence are being positioned for bringing the same kind of changes for the business world (Farrugia 2017). Previously, organizations have been spending numerous days to provide an answer to queries that could be answered easily interpreting the individual data of the company and to prepare and analyze information that is manual and complicated processes (Wang 2015). For the upcoming years, a significant transformation is the area of data analytics can be seen. This has been enabling business users and analysts to answer a question at any instance.

Metadata layer

Next, business intelligence is helpful for data visualization. This has been effective to compile lists flow vital data points and utilize spreadsheets for organizing and making sense of information. However, executives, business users and salespeople have been demanding quick insights and have been providing more through visualization tools. This has been offering a broad range of methods for viewing data (Kimble and Milolidakis 2015). Moreover, as more data sources have been emerging, additional methods are there to see where data has been appearing.

Further, there is self-service business intelligence. This is the main benefit of current BI and data visualization tools. Here, the users have been able to leverage various self-service tools of visualizations for creating primary charts and graphs for some period. Besides, it has been proven to be sufficient for users who need to move deeper into data. Advanced self-service abilities have been enabling users for creating visualizations that have been much more complicated. These are much more complicated such as complex measurements, forecasting and trends (Akhtar,Humphreys and Furnham 2015). These are also diverse concerning geospatial displays, heat maps and funnels and has also been interactive such as supporting real-time streaming of data, custom filtering and various user-defined drilling down. As far as mobile business intelligence and developed information access is concerned this has been the norming in consumer space for accessing the data needed as one requires that. This has been irrespective of place and time. Here, for any time, thus, users of business has been demanding similar functionality for various enterprise applications.

This proper information at the appropriate moment has been helping to clinch deals making other sales and serving customers for profitably and retaining business that has been lost. In case this has liberating current dashboards from re-architecting and desktop, the compile workflows across mobilizing primary business data, various organizations have been getting the advantages of mobile business intelligence (Bodislav 2015). Then there are customized applications with built-in business intelligence. Different off-the-shelf BI and tools of analytics have not fit all use cases. It is also seen that more users have been creating various customized applications having embedded BI and components of data visualizations. It is vital as it has been taking the designing of various visualization tools especially under the hands of BI specialists. This has been allowing using those tools for deciding how they have been consuming data. Here, the implementation has included various applications of business intelligence that custom-coded including customized applications from multiple off-shelf BI platforms and components of BI that are embedded under transactional and operation applications.

Business Intelligence, in a broader sense, refers to the set of technologies, applications, methods and ideas. These are sued for transforming raw data to meaningful one. This is used by stakeholders for making informed decisions. BI techniques, tools and practices are used by organizations for understanding the situation of affairs, market conditions and competitors. This is helpful to address current concerns of business and create strategies of the organization. This has been providing competitive advantages in the marketplace (Torres, Sidorova and Jones 2018). For making informed decisions, the data of organizations has been accessible to all kinds of stakeholders who are relevant. Here, the accessibility has been assuring business users to go through their analysis which has been sharing insights freely with their team members. Further, BI systems have been managing organizational metrics and presenting them to various decision makers across intuitive dashboards, self-service capabilities and reports. This data analytics and data management elements of BI systems have been consolidating complicated internal and third-party from various applications to the core framework for converting other metrics and performance indicators.

Ranking reports

It has been combining data that are analyzed in details and compared to multiple other performance indicators and metrics (de Jager and Brown 2016). Though the enterprise project management solution and system, internal project management teams and consulting companies have different other business has been delivering services of project management, these have often been failing to meet those aims. Here, without any meaningful method of establishing goals and tracking milestones with project results, enterprises are unable to understand mistakes, forecast resources and then predict revenues and develop a competitive position in the market (Laursen and Thorlund 2016).

Here, the software of project management and procedures has been providing information and data with which teams, executives and project managers have been able to track and analyze the success of projects. Besides, the systems have been falling short to deliver drastic analytics, features of critical security and flexible perspectives for enabling business users to fetch information that has been meaningful to them. A few systems have been providing elements of needed features and various functionalities. They have been offering aggregated data for evaluating and monitoring outcomes and trends for teams, projects, processes, individuals and performance on series of times (Chung 2014). These solutions have been providing automated alerts and various personalized dashboards have the latest information that is integrated from enterprise data sources for assuring that user that the data they require for proper corrective actions and know the actual status of a project team and all kinds of activities with interdependent tasks.

Actual business intelligence helps in a project team and project managers in managing milestones and various types of project timelines at an individual level of the projects. This takes place around the project such that multiple project factors, reporting and equipment and resource allocations gets optimized. Here, aggregation of project information helps teams to manage numerous projects in a better way for any single client and various clients. Then it has been drilling down data for activity, only squad and task (Tole 2015). Here, project managers can share data and drill down with the KPI. This is done for project management templates for finding the root reason behind the problem, evaluate tactically and establish strategies with operational results at summary levels. This takes place at a detailed level for an individual task or any contributor. Any elegant BI and CPM or Corporate Performance Management solutions have been flexible with tools that are browser based. These are accessible from the enterprise and over the road. The deployment has been fast and straightforward and here equipment of training are minimal. This is also for average business users. Here solution of business intelligence has been providing an integrated view of data having an intuitive flexible display. This is personalized to all business users. Here, teams have been efficiently combining and displaying data for ERP, various project managers and systems for creating a unified viewpoint of results and performances (Höpken et al. 2015). Here TCO or total cost of ownership has been low and ROI or return on investment has been tremendous. Here, users can use complicated features in a simple scenario to forecast and various tasks like delivery of alerts, personalized publishing which is automated, presentations, reporting and predictive analysis and so on.

Functions of Business Intelligence

BI has been permits customization and consolidation of information needed for making the decision. It is a helpful strategy process and optimize operations of a business. This also includes figures required and information for incorporation that are spread out across the market. Further, seeking the proper scenario for all users is trickier than it has been sounding. This is because every user has been interacting with information that never possesses similar needs (Maté et al. 2016). This needs a healthy level of strategic insights and various c-level day-to-day required tasks for different details. For implementing BI, the problem to produce dependable and vital figures are necessary to get addressed. In many cases, there has been an uncertain origin of data that has been resulting in conflict to reports. Here, there are scenarios. Here the frequency of data collection and the content of statements have not been aligned with the perquisites of stakeholders. It has been resulting in a lack of trust of business owners with data retrieved from reports (Stone and Woodcock 2014).

However, it must also be reminded that business intelligence and portfolios of projects have never been a system or a product. This has been consistently evolving architecture, vision and strategy continually determining to align the direction and operations of the business with strategic business aims. It is seen that business intelligence is a wide area. This has been encompassing capturing of data, data warehousing, performance management, cleansing with dashboarding and reporting (Marjanovic, Dinter and Ariyachandra 2017). Focusing on various reporting aspects of BI has suggested different tools. This is to find various communication and reporting necessities for portfolios of projects. This is helpful to create BI solutions, Moreover, this has enabled portfolio managers to develop informed decisions. This application of BI towards portfolio management has been helpful for portfolio managers, teams and various stakeholders for understanding the way in which portfolio is done in due time and decisions are taken for assuring that balance of portfolio is optimized and maintained.

Here, efficient communication and reporting are seen as the primary element for developed decision making. Further, it has been vital that collection of data and dissemination frequency, communication mechanisms and content of reports get aligned with requirements of stakeholders. Here, the stakeholders have not been searching for data. Instead, the information has been presented to them from needs (Puklavec, Oliveira and Popovi? 2014). Additionally, the reports have been submitting data has been assisting stakeholders in creating informed decisions. Here, project portfolios have been developing strong data that has been lost due to inefficient capturing and mechanism of dissemination. Further, data captured has not been circulated in an optimized way. The BI capabilities and dashboards of portfolios have been delivering interactive and summarized information. These have been consolidating, aggregating and arranging portfolio and project measures. These are vital for stakeholders. Thus the capabilities have been used for displaying proper information for an adequate audience over any single screen.

Conclusion: 

The above study shows how business intelligence is developed to take everyday data to organizational operations. Thus, it can be concluded that, BI can be utilized for developing business. Thus using this otherwise ignored information has been improving the performance of business under a win-win situation. This situation is for every people who are involved. By summarizing the overall study, it can be said that business intelligence is a comprehensive term denoting all the elements related to the collection, processing and using raw data that are received by business all the time. Thus using this disregarded data has been developing the way in which company has been operating and thus BI has been turning to be dominant. Here, various stages are included in business intelligence ranging from a collection of unprocessed information for drawing favorable conditions. At last, despite that fact that BI has seemed to have the own language, there have been just some initial terms that are needed to understand to start an individual journey of business intelligence.

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