What Is Business Intelligence's Role In Big Data Analysis


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The Fundamentals of Business Intelligence is a comprehensive overview of data and data analysis. The guide explains the types of data available to businesses and how these data types work with one another to provide insights to large companies. Look beyond the hype of big marketing to understand the role of all types of data and understand what big data is in the right context.

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What Is Business Intelligence's Role In Big Data Analysis

  1. 1. A Comprehensive Overview Of BI In Today’s Data Driven World The Fundamentals of Business Intelligence Presented by Beyondsoft
  2. 2. “Businessintelligence(BI)isaconceptthattypicallyinvolvesthedeliveryand integration of relevant and useful business information in an organization. Data mining is nothing new, but in the last three years, companies have come to realize that BI is much more than corporate reporting from an information house in the IT department. With the advancements in visualizing information, data can be accessed and used across the organization to cut costs, streamline organizational efficiencies, refine products and services, and launch new ones. BI continues to be one of the fastest moving areas in the enterprise. So, how do mid to large size companies decipher just what data the organization should be looking at? Additionally, how do they decide what to do with it? In this comprehensive guide, we outline all you need to know about data, analysis, and business intelligence. Introduction to Business Intelligence — Alvin Yang, Sean Clemmons, and Robert Newman http://www.beyondsoft.com http://blog.beyondsoft.com
  3. 3. 1 The Fundamentals of Business Intelligence Business intelligence (BI) is a system of tools and methods that aid in strategic planning and informed decision-making. This process starts with extracting raw data and outputs actionable information that when utilized properly, can provide benefits throughout the organization. Although the breadth of a BI system differs from company to company, possible components from end-to-end include: What Is Business Intelligence Information Discovery and Management The process of collecting data and preparing it for analysis. Data is extracted from internal and external sources, data provenance, data governance, data dictionaries, and ontology. Intelligence Running queries, DSS, intelligence systems, A/B testing, and employing machine learning in order to analyze data to gain insights. Visualizing data relationships for decision makers Produce graphs and charts to represent insights derived from comprehensive analysis through dashboards, GIS, and visual analytics in order to distribute to decision makers and their teams.
  4. 4. 2 The Fundamentals of Business Intelligence Data is raw or unorganized information that is the essential building block of any business intelligence system. Data is source material with the potential to provide continuous discovery. Typically, data comes from one of four sources: PRIVATE Data from within the company, such as proprietary data, that is usually the first to be gathered. Understanding Data STREAMING Data transference from interconnected devices that are mined as data arrives. SOCIAL MEDIA Unstructured or semi-structured information derived from online social interactions. PUBLICLY AVAILABLE Information acquired from open sources, such as data.gov or the CIA World Factbook. 1 2 43
  5. 5. 3 The Fundamentals of Business Intelligence Data on its own –– no matter how well managed, processed, and governed –– holds little value. Value derives from the analysis of data sets and from the insights that arise during the analysis. Effective analysis involves finding meaningful patterns in the data and relating those patterns to the business context. There are four general types of analysis that organizations can employ: Descriptive Analytics: This most basic form of analytics involves using historical and real-time data to find overall tendencies and learn from past behaviors. It is the building block for subsequent types of analysis. General examples of descriptive statistics include sums, averages, and percentage changes. By using descriptive statistics, companies can answer: What happened and why? Understanding Data (continued) Predictive Analytics: Once descriptive statistics are in place, analysts can combine historical data with predictive algorithms to make predictions about future outcomes. Predictive analytics can help with planning and goal setting. Predictive analytics can answer: What might happen next? Keep in mind that the insights derived are only probabilities. Prescriptive Analytics: This type of advanced analytics inserts predictive analytics into a business context to optimize decision making. Examples include business rules, algorithms, machine learning, and computational modelling. Prescriptive analytics presents projected outcomes for potential actions, providing insights on what to do next. Diagnostic Analytics: Diagnostic answers the question of how and why of something has happened or is happening. In order to produce insights, it leverages techniques such as drill-down, discovery, mining and correlations to find patterns and trends. Diagnostic analytics can be used to provide an understanding on cross-functional data, thus enabling strategy development revolving around cost, profit and risk, and performance variations.
  6. 6. 4 The Fundamentals of Business Intelligence Help you understand customer behavior: The use of data streamlines business functions in many ways. According to Datameer, 48% of companies use it to conduct customer analytics, 21% use it for operational analytics, 12% use it to prevent fraud and ensure privacy compliance, and 10% use it to create new product and service innovation. Improve your product: Through product data analysis, you can identify and address quality or inconsistency issues in your product and increase efficiency of product development. By developing alerts to continually monitor for anomalies, you can identify product vulnerabilities and remedy the situation proactively, maximizing revenues. When new features or enhancements are added, you can ensure that the design of each feature is done with an eye on the information gathered in reporting and analysis. What Can Business Intelligence Do for You? Improve company efficiency: Data helps shed light on where efficiencies can be improved. This can include one or more areas like overstock, slowed production, and low employee satisfaction. It can also prevent short-term bottlenecks from becoming bigger problems. By having a centralized data system, you can quickly identify causes of problems from the source and tackle them immediately. Gain competitive advantage: By analyzing performance data against competitors, you can determine where you are outperforming and underperforming other businesses in your market. With BI mapping tools, you can visualize how you compare in shared geographical areas. These insights can help you decide whether or not to expand to a new area and where to focus marketing efforts.
  7. 7. 5 The Fundamentals of Business Intelligence Improve sales: By leveraging sales-related data, you can enhance your sales strategy, yielding bigger returns and anticipating future issues. Comparative analysis can identify gaps in sales, capitalizing on areas that are propelling revenue and troubleshooting in low-performing areas. BI mapping provides insight into customer demand, suggesting where to funnel efforts and which new endeavors are smart for your business. Improve marketing: Marketers have utilized BI for years to achieve a variety of gains. Some of these include: analyzing social media to determine where to focus efforts, assessing ROI to discover what motivates consumer behavior, and segmenting the market to build brand. Recent advances in audience targeting enable markets to align their strategies with customer sentiment and trends. What Can Business Intelligence Do for You? (continued) Gain user visibility: By having a comprehensive BI strategy in place, you can gain visibility into every facet of the company. This is especially important within complex supply chains that involve a plethora of users and factors. This visibility leads to enhanced reporting and informed decision making across all levels. Turn data into actionable information: Through analysis, data is interpreted and enriched. When this analysis is outputted in reports, insights and recommendations become visible and bring the data into the business context. BI tools place these reports in the hands of high and low level decision makers, helping them see what the best course of action is. By focusing on KPIs, you can track progress on those factors that are paramount to reaching your goals. BI bridges the gap between the data analysts and the business users.
  8. 8. 6 The Fundamentals of Business Intelligence How to Determine If You Need BI The Economist Intelligence Unit reports that 48% of organizations using BI feel that they have missed opportunities to make the most of their data. To avoid missed opportunities, look for these three major indicators that your organization needs to revamp its BI system: Data, but no information: This means that you have a wealth of information, but need assistance aggregating and analyzing it. You cannot turn data into actionable insights because you are missing the intelligence part, the operations that make this data valuable. Relying solely on IT for reports: If you are constantly pestering the IT department to produce reports, you are needlessly keeping them from doing other important work. Data should be brought to those people within the business who can utilize it. By implementing an easy to use BI tool, those making the decisions can do the work themselves, leading to faster decision-making and freeing up IT for other tasks. Using spreadsheets without BI software: Spreadsheets do not present data in real time and are often isolated. If you are only using Excel, you are missing out on the speed and ease that BI tools provide for combining data from many sources and sharing and updating reports.
  9. 9. 7 The Fundamentals of Business Intelligence How to Determine What to Track According to Alvin Yang, Senior Vice President at Beyondsoft, “Once data is prepared and cleansed, BI professionals must determine what to measure, which changes over time depending on current goals.” Tracking too many metrics leads to dashboard overload, which can cause significant data to be lost in the noise. Worthwhile metrics to track are simple to understand and use, can be replicated effortlessly, and present valuable, actionable information that impacts the business. When determining what to track, consider these types of metrics: Qualitative vs. Quantitative Qualitative metrics provide intangible information, such as survey responses and customer feedback. They provide behavioral insight and answer how and why. Quantitative metrics are hard data and statistics that can be aggregated and evaluated to show trends. They show the who, what, and where. These metrics are better to follow because they are more objective and easier to analyze. Vanity vs. Actionable Vanity metrics make a company look good, but do not hold much meaning because they can easily be manipulated. They are best to avoid when decision-making. However, by asking questions like “Where are users going when they leave the page” they may lead you to discover actionable metrics to follow. Actionable metrics are tied to tasks and are specific to goals of the business, such as revenues or number of active users. They provide guidance on what might be going wrong in your business. Actionable metrics do not necessarily solve problems, but they do point you in the right direction.
  10. 10. 8 The Fundamentals of Business Intelligence How to Determine What to Track (continued) Reporting vs. Exploratory Reporting metrics include typical reports that reveal what is happening in an organization, such as how many products were sold over a given time. On their own, they may not lead to any actionable discoveries, but they are good for measuring progress. Exploratory metrics require searching through information to uncover a solution to a problem that may be hidden within the data. These metrics require more user effort, but they can lead to powerful discoveries. Correlated vs. Causal Correlated metrics involve examining metrics that change simultaneously to make predictions. Causal metrics involve experimenting to discover the cause of a correlation, giving you the opportunity to influence it. Finding causality is difficult because a correlation may be influenced by multiple outside factors and require a great deal of experimentation to determine. Lagging vs. Leading Correlated metrics involve examining metrics that change simultaneously to make predictions. Causal metrics involve experimenting to discover the cause of a correlation, giving you the opportunity to influence it. Finding causality is difficult because a correlation may be influenced by multiple outside factors and require a great deal of experimentation to determine.
  11. 11. 9 The Fundamentals of Business Intelligence Beyondsoft Sports (Sounders) Case Study The Seattle Sounders entered 2015 with high expectations following the most successful season in the club’s history the year prior. By the standard which they laid out for themselves, the 2015 season must be classified as a failure. While the team’s results can help tell the story at the highest level, in order to properly assess the causes of the team’s shortcomings in 2015, a closer look at the numbers that led to those results is needed. The key questions needing to be answered heading into the offseason relate to whether or not the 2015 season’s results are likely to be repeated. Putting the data into its proper context is vital to performing the proper analysis. Implications The data behind this Power BI report has been compiled from publicly available sources. The majority of the information comes directly from the official website of Major League Soccer. Schedule and venue information comes from official team websites. Geolocation data has been pulled from Wikipedia. All-up statistical information shows a player’s impact over the course of the full season, while per-90- minute rate statistics allow an individual’s contribution to be projected over the course of a full season. This is crucial in evaluating this season in particular, as many key players were unavailable for long stretches of the season at a rate far exceeding what would typically be expected. Looking at team-wide, per-game statistics over time also highlights the difference in performance between the team at full-strength and the team in a weakened state. The metrics contained within this report help to tell a more in-depth story than a glance at the final table. They also help answer some key questions about the causes of this year’s struggles. Given the variety of data points included in the model, the available metrics can help to adequately tell the story of past or future seasons as well. The following custom Power BI dashboard displays an analysis of the Seattle Sounders 2015 season, and shows how data can be used to create visuals that answer questions.
  12. 12. 10 The Fundamentals of Business Intelligence Beyondsoft Sports (Sounders) Case Study Dashboard View 1 Shows: General season results overview: the team’s progress by month Answers: Did they improve or get worse? At what points in the season were they lagging? How can this information impact decisions?: This information can impact training decisions and determine pacing throughout the season depending on what parts of the season saw lower performances. Dashboard View 2 Shows: Breakdown of high-level metrics by game location Answers: In which locations did the team play better? How can this information impact decisions?: Worse performance at away games can suggest utilizing better performing players for longer during away games. Better performance at home games, or in certain other locations, can suggest resting better performing players at the start of the game and utilizing them later, if the team falls behind. Dashboard View 3 Shows: Statistics by individual player Answers: How important was each player to the club’s success? How can this information impact decisions?: This shows which players improved throughout the season and deserve more playing time, as well as who performed better under pressure. It also reveals which players fell in performance and why that may have happened. For coaches, this can determine who deserves more playing time and where on the field and when during the game and/or season to utilize each player.
  13. 13. 11 The Fundamentals of Business Intelligence The Future of Business Intelligence Moving forward, understand company data is going to be paramount to success. According to Sean Clemmons, GM of Data and Analytics at Beyondsoft: On a larger scale, the cloud is finally settling down into a high quality tool for BI to leverage, rather than the latest tech cure-all. Moreover, customers are asking for intelligence divisions and agency partners to help them understand what parts of their data should move to the cloud, what should stay on permanently, and how to bring those sets together into high quality information. On another front, self-serve business intelligence remains a carryover theme from previous years; ensuring the industry is getting the information in the hands of the business, not just IT. The skillset to comprehensively leverage BI requires more business understanding than in IT and more tech knowledge than is typically found in business. The progression of Qlik, Tableau, PowerBI, and others have made self-serve BI less of a reach. Today, the tools to create good BI have become less expensive, more attractive, and easier to use. That said, the volume of data behind them has grown exponentially, which creates its own challenges. As more companies produce positive results like these, staying afloat among competitors requires assessing your system and replacing outdated tools and tactics. “The overarching goal of business intelligence is to swiftly deliver pertinent information to those who can use it to make key decisions that will generate progress towards the company’s objectives,” says Peter Huang, Director of Data and Analytics at Beyondsoft. “To see positive return on your BI investment, these objectives must be clearly defined beforehand and kept in mind throughout the process – from strategizing, to choosing tools, to determining KPIs to track,” he adds. To ensure your efforts are comprehensive, reach beyond diagnostics and aim to predict future outcomes and prescribe potential solutions, maximizing insights that can positively impact present and future business. Do you want to learn more? Visit blog.beyondsoft.com or contact us at Beyonddata@us.beyondsoft.com, to see how Beyondsoft can make your data work better for your organization.
  14. 14. 12 The Fundamentals of Business Intelligence Who is Beyondsoft Beyondsoft is a global IT Consulting, Solutions and Services provider. Founded in 1995 and headquartered in Seattle, Washington, Beyondsoft has over 30 global offices, R&D bases and delivery centers, as well as facilities in United States, Japan, China, India, Canada and Singapore. Relying on its strong R&D heritage and ability to innovate, we are now focusing on using emerging, disruptive technologies, such as cloud, mobility, big data and analytics, to provide powerful solutions and products for clients in a wide range of industries including: high-tech, e-Commerce, finance, automobile, retail, logistics, energy, manufacturing, healthcare, telecommunications, media & entertainment, and travel. Our comprehensive worldwide delivery and service network is built on years of deep industry experience and business process excellence. It’s supported by an international team of experts with the practical abilities, dedication and innovative spirit to help global clients achieve and maintain the highest levels of operational excellence and profitability, and to continuously create value for their stakeholders. The management team is headed by Alvin Yang, Senior Vice President at Beyondsoft. Learn more about Business Intelligence, Beyondsoft and industry trends by following us on social media: Twitter: twitter.com/beyondsoftUS Facebook: facebook.com/beyondsoftUS LinkedIn: linkedin.com/company/beyondsoft YouTube: youtube.com/channel/UC6f- WNxipK3R9EschRo5RExA Instagram: instagram.com/beyondsoftUS
  15. 15. 13 The Fundamentals of Business Intelligence References Halper, Fern. Four Reasons to Analyze Customer Behavior. TDWI Research. August 25, 2015. Kondo, Naka. The Business of Data. The Economist Intelligence Unit. January 12, 2016. McKenna, Brian. Amadeus Aims to Add More Business Intelligence to Travel Industry. Computer Weekly. July 7, 2015. Popky, Linda J. Identifying the Marketing Metrics That Actually Matter. Harvard Business Review. July 14, 2015. Steinberg, Leigh. Changing the Game: The Rise of Sports Analytics. Forbes. August 18, 2015. 2015 State of the Industry. Datameer. 2015. 2015 Supply Chain Report. Raconteur. 2015.