Business Intelligence

Getting Started with Dataflow in Power BI: Creating Your First Dataflow

Dataflow is a comprehensive way to deal with large datasets and reduce the load on data analytical tools/software like Power BI. We’ll discuss the need for dataflows, ways to create them, and the uses of dataflows for a business. Power BI is a popular data analytics and data visualization software developed by Microsoft. It is a collection of apps, software services, and connectors that collect, process, store, and analyze data to deliver reports in real-time. There is much more to Power BI than its definition. That’s because Power BI deals with the continuous inflow of data from multiple sources. The accuracy of the reports generated by the software depends on the quality of the input data. Cleaning, sorting, formatting, and streamlining data within the system is essential to get actionable insights. This gets harder when the business has to deal with large datasets. When you add large volumes of data to a system, you need to take extra care to maintain the overall quality. Setting up dataflow in Power BI is a smart solution to manage input data and ensure accurate reports. In this blog, we’ll read more about the problems caused by large datasets and how dataflow solves the problem. Issues with Large Datasets in Power BI Dirty data or unclean data is a real problem in today’s world. We have access to countless information sources. But how good is the data from each source? Errors, redundancy, unwanted details, etc., need to be identified and cleaned before the data is used for analytics. Big Data Data with greater velocity, variety, volume, etc., that cannot be processed by traditional systems is known as big data. Processing unclean big data requires a higher computing and statistical power that can increase the expenses for a business. Spellings and Missing Values Misspelled words or missing characters/ values can change the context of data and lead to the wrong analysis. Identifying these errors in large datasets is time-consuming and effort-intensive. Lexical Errors The difference in data structure between two or more data sources can create confusion when formatting the data into a single structure. Imagine what would happen if one field was attributed to another. Mismatches and Contradictions Data from two sources might contradict each other based on the parameters used. Common abbreviations have multiple meanings, and each source might refer to a different one. Money could be measured in different currencies. Changing the values and correcting them in a large dataset can be a never-ending task. What is Dataflow? Dataflow is a way to prevent issues with large datasets in Power BI. But what is dataflow? The term dataflow has quite a few meanings. Microsoft defines dataflow as a collection of tables that are created in the Power BI workspace. Any number of tables can be added to the dataflow. The existing ones can be edited to correct and update the information. According to another definition, dataflow is a process running in the cloud and not related to any particular Power BI report. The dataflow can be used for numerous reports simultaneously. That means five or ten employees can send a query to the same dataflow at the same time and get the information they require. Since dataflow runs on the cloud, any changes required will not have to be made to all the reports but only to the data in the dataflow. Another explanation of dataflow is comparing it to a typical river or a water body. Just like a river has different sources and stops but ends at a single destination, data in the system also comes from different sources but gets stored and used in the data warehouse/ data lake for analytics. By releasing data from silos and removing barriers, it will create a seamless data flow within the enterprise. When this data is used for querying in Power BI, it will provide better and more accurate insights. Why are Dataflows Important? We now know what dataflow is. But why is it so important for a business to create dataflow in Power BI? What changes does it bring to the business processes? Let’s take a look. Reusability The biggest advantage of creating dataflows is to reuse them multiple times. You don’t have to create a new dataflow for each report. You also don’t need to remove/ delete old dataflow and create a fresh one because of outdated information. One more advantage is that you don’t have to create new data connections each time (both on the cloud and on-premises). Seamless Integration Dataflows can be integrated with existing systems and tools in the business. Dataflows work seamlessly with Power BI as you only have to set up the connections and run queries. Cost-Effectiveness Your Power BI premium subscription is enough to create and access dataflows in data lakes. If you don’t use Microsoft Azure, there’s no need to start using it only for dataflows. There won’t be any additional expense to pay for licenses. Scheduling Data Updates Keeping data up to date is necessary to generate real-time reports. You can track the updates and changes made to dataflow and schedule the refreshing of the tables. Furthermore, you can build different processes to manage dataflows and save them in different places. Short-Term Data Storage A dataflow also serves as a temporary data storage center. Processing a large data file/ database doesn’t require extra time. The data can be stored in dataflow for the time being to speed up the analytics and deliver timely reports. How to Create Dataflow? Here’s how to create dataflow with new tables that are hosted on OneDrive Business: Results of Using Dataflow in Power BI Dataflow reduces the load on Power BI by taking over the transformation layer. Since the tables in dataflow can be edited and reused multiple times, dataflow can be used with many applications within the enterprise. The dataflows can be connected to other Microsoft Power Platform technologies Power Query, MS Dynamics 365, Power Automate, Power Apps, and so on. What are the Uses

Business Intelligence in Manufacturing: Transforming the Industry

Data-driven manufacturing is the need of the day. Digital transformation has entered the manufacturing industry and is changing the sector through data analytics. Business intelligence is the key to revamping manufacturing and improving quality, production, and returns. The manufacturing industry has been looking at business intelligence with renewed interest. Data is usually scattered in the factory and manually fed into the system; it’s also offline until it is entered into the database. Business intelligence provides a solution to bring the data together with minimum effort. It promises data collection, cleaning, and analytics to improve the manufacturing processes and increase returns. The manufacturing industry contributed 18% of the GDP in the Middle East in 2018. The countries have marked manufacturing as an integral part of their economic strategies to achieve their 2030 visions. The ME region has the necessary infrastructure and connectivity to boost the manufacturing industry. Oxford Economics said that UAE’s industrial sector grew more than a third during the 2007-17 decade. Innovations and technological adaptations have been game-changers. Artificial intelligence, business intelligence, data analytics, etc., are said to take the manufacturing industry in the Middle East to newer heights. The Gulf countries are using business intelligence services offered by offshore companies to revamp their existing systems and make the necessary changes to stay active in the competitive market. Let’s read in detail about the role of business intelligence in manufacturing and how data analytics can help manufacturing industries fulfill their role in contributing to the 2030 economic vision of the Middle East. Types of Manufacturing Processes In simple terms, manufacturing is the process of producing products/goods using raw materials and tools. Biological or chemical processing may also be used to obtain the final product. Be it the production of a tiny toy, household appliances, or an automobile, converting raw materials into finished goods by following a systematic and pre-defined procedure is known as manufacturing. However, the reality is much more complicated and involves a range of factors such as quality, cost, production cycle, duration, supply chain, and more. The path from acquiring raw materials to supplying finished goods to the market is filled with various elements that are not always under our control. Furthermore, the manufacturing processes are classified into three types: Make to Stock MTS is where the finished goods are made in large numbers and held as stock in stores. These are widely used and always in demand. That said, manufacturing too much in surplus can lead to blocked capital and losses. Make to Order MTO is where the manufacturer waits for an order to start the production process. The clients/ customers have to wait until the production cycle is complete and the end product is handed over to them. Make to Assemble MTA is a combination of MTS and MTO. The manufacturer has a stock of the parts required to assemble the final product. The assembling will be done only when an order is placed. This not only reduces the time to deliver the product to the customers but can leave the manufacturer with excess parts if there are no orders. How a manufacturer manages the processes and stock determines the success of the business. Business intelligence helps manufacturers use historical and real-time data to correctly anticipate the market demands and adjust production accordingly. What is Business Intelligence? Business intelligence is a set of procedures, techniques, and software used to convert raw data into meaningful insights. BI allows manufacturers and enterprises to increase their business efficiency by making required changes to their systems and processes. Every industry requires business intelligence to analyze data and derive actionable insights. These insights help businesses to make better decisions in a quick time and stay relevant in the competitive markets. Business intelligence is the use of data and data analytics to gather valuable information. BI for the manufacturing industry is also called manufacturing intelligence or manufacturing analytics. Business Intelligence in Manufacturing Industry The manufacturing industry needs to streamline and balance machine operations, supply chain, and logistics to get the desired results. The main aim of the manufacturing industry will be to reduce production costs without compromising the quality standards or delaying the production cycle. To achieve the goal of reducing costs and increasing production, the manufacturer needs to rely on the data-driven model to make decisions. This is possible when the data flow is aligned within the manufacturing unit and bridges the gap between data, systems, and employees. BI and data analytics give manufacturers the necessary tools and insights to use data effectively and make the right decisions for the business. How is Business Intelligence Used in Manufacturing? The use of business intelligence in manufacturing can be seen at every stage, from sourcing raw materials to supplying the final goods to end-users. Since most manufacturers already have the ERP system in place, adopting a BI and data-driven model is not too complicated. Hiring the services of a business intelligence developer will help manufacturers understand the ways to implement BI and data analytics to derive accurate insights. Improve Operational Efficiency Operational efficiency is a must for a manufacturer to survive the competition in the markets. However, it is possible only when a business knows what changes to make and which processes to continue. While data is available in abundance, using the data efficiently to gain in-depth insights into the existing operations of the manufacturer can be achieved through business intelligence. BI reduces the time taken to analyze data and derive reports, thus providing the management with the necessary information to make changes on time. Manage and Streamline Supply Chain A manufacturer works with various third-party vendors, suppliers, carriers, distributors, etc. A delay at any point in the supply chain will lead to disruptions, postponements, and losses throughout the production cycle. It could lead to product failure or put the manufacturer at a disadvantage. Business intelligence gives insights into suppliers, transporters, deliveries, expenses incurred during distribution, and so on. The reports can be used to choose reliable suppliers and freight partners and plan the production

Management Information System Vs. Business Intelligence: How is BI Better Than Traditional MIS

MIS is a traditional information system used to collect and process data. BI is an umbrella term covering various processes and technologies that empower an enterprise to use data effectively and make the right decisions. Before business intelligence took over, many enterprises had another information system called the MIS. Management Information Systems were the heart of every business and played a vital role in data collecting, storage, processing, and reporting. However, MIS had its disadvantages and became a burden for many businesses. With business intelligence entering the market, enterprises adopted BI, not to replace MIS but to revamp their entire internal system. MIS is a small part of the business intelligence framework and is no longer enough in the competitive world to help establishments make the right decisions. Let’s read more about MIS and BI in detail and understand how BI is a better and more comprehensive alternative to traditional MIS. What is Management Information System or MIS? MIS or Management Information System is based on an old concept where data is collected from various sources, compiled, and presented in a readable format. It is used by mid-level and top-level managers to make the necessary business decisions. MIS is a collection of systems and processes that facilitate data collection, compilation, and reporting within the enterprise. The definition sounds similar to what a BI tool does. However, the difference lies in the technology used, the approaches to data collection, storage methods, and reporting formats. Before we read more about the differences, let’s take a brief look at the different functions of MIS. Data Collection: Different types of data can be collected by MIS. Financial information, employee details, sales figures, etc., can be sent to MIS, which is integrated with other software used by employees. Decision Making: MIS is used to help with decision-making. It presents aggregate data reports that help the top management make day-to-day decisions. Collaboration: Employees can be provided access to edit and share the data stored in MIS. The MIS department handles the everyday issues related to the system. Business Reporting: Managers make decisions based on the business reports generated by MIS. Even non-managers can get reports to compare data or compile a data file. What is Business Intelligence or BI? Business intelligence or BI is a wider concept that combines MIS, business analytics, data mining, data visualization, and much more. It is a modern framework that helps enterprises adopt the data-driven model to make better decisions based on historical and real-time data. BI gives businesses a comprehensive view of the enterprise data and makes use of this information to understand market trends, improve customer experience, evaluate existing policies, and make changes to build a better enterprise. Today’s BI tools and solutions offer self-service analysis to employees from different levels in the organization. Business intelligence tools are flexible, scalable, and user-friendly. Here’s what the BI framework handles in an enterprise: Data Mining: It is the process of analyzing large volumes of data to gather more information. Datasets, statistics, and machine learning are used for data mining. Data Preparation: Data from internal and external sources is collected, cleaned, and formatted to keep it ready for data analytics. Types of Analytics: Business intelligence is capable of providing different types of analytics based on the organization’s requirements. For example, preliminary data is used for descriptive analytics; descriptive analytics data is used for statistical analytics; predictive analytics is a combination of statistical analytics, data mining, and machine learning. Querying: An employee asking the BI tool for specification information is called querying. The tool uses computing power to collect data from datasets and processes it to provide an answer to the query. Data Visualization: Visualization is the technique of presenting data in a graphic form in real-time. The reports generated by the BI tool are presented in charts, graphs, holograms, heat maps, etc., for easy understanding. What is the Difference Between Management Information System and Business Intelligence? MIS and BI are interrelated. They have common elements, though BI is an umbrella term that encompasses a range of processes and tools used to implement the data-driven model in an enterprise. Scope and Focus Management Information System or MIS is a part of the business intelligence framework. Traditionally, enterprises used MIS mainly for revenue and expense reporting. However, they had to face several issues with inaccuracies, inconsistent data, and other system complications. While business intelligence deals with the analysis of products and customers, MIS is used to analyze the business in terms of finances. Difference in Reporting MIS delivers aggregate data reports which are not enough to get a complete picture of the business situation. It doesn’t offer in-depth insights that help the managers identify the problem. For example, the MIS report gives aggregate data about income and expenses. This doesn’t include transactional data that are key to identifying the root cause of the issue. The managers have to run multiple queries to gather the relevant information. Business intelligence tools provide in-depth analytics for the given data. Moreover, the reports are generated in real-time. The dashboard of a BI tool allows employees to get a macro and micro view of the same report just with a few clicks. Business intelligence not only works faster but also requires lesser computing power as it has a higher processing capacity. Self-Servicing Business intelligence tools allow self-servicing within organizations by empowering employees to access data and run analytics as and when necessary. The dashboards can be accessed from different platforms such as web browsers and mobile apps. While MIS is complicated and confusing, BI is elaborate yet efficient and user-friendly. Automation is possible with business intelligence. MIS and Business Intelligence: What’s the Connection? Management Information System has a narrow range of services, and business intelligence deals with a wider and broader scope where different aspects of the business are taken into consideration. Furthermore, BI is an advanced and modern framework that uses the latest technology to deliver accurate insights and reports. The disadvantages of MIS are solved using the BI tools. Accurate Insights: Unlike MIS, the reports generated

Power BI Supply Chain Dashboard: What Can It Do for Your Business?

Supply chain analytics helps businesses understand their datasets to make informed decisions about their logistics and transportation processes. Power BI is an incredibly useful business intelligence tool to create supply chain dashboards and use the insights in real-time. Let’s discuss the role of supply chain analytics and Power BI in various industries. The supply chain is a network of people, businesses, and processes that ensure that a company continues to produce and sell products/ services in the market. From sourcing raw materials to moving finished goods to the warehouse and delivering them to the end customers, the supply chain network is intricate, complex, and systematic. The implementation of the supply chain strategy has an impact on the success of a business. After all, how can a company deliver the products/services to the end-users if it cannot source the materials or transport the finished goods as per the schedule? Covid-19 has disrupted the global supply chain, and the Middle Eastern markets, too, faced the same trouble. Challenges such as shortage of labor due to lockdowns, increase in demand, and reduction in supply and adhering to the safety protocol makes it difficult for businesses to manage their supply chain. However, the companies also know a solution to the problem. Many Middle Eastern businesses are heavily investing in technology, especially artificial intelligence, to make their supply chains more resilient even in adverse conditions. For example, Hypermotion Dubai is an ME edition of the German-initiated convex that gives the transportation and logistics industries a fresh start. The aim is to be sure that the emirate continues to lead in supply chain management and speed up development. The Dubai-based global logistics company, Aramex, has built a data lake and streamlined its supply chain process by relying on machine learning. This led to a whopping 74% increase in shipping accuracy. It also resulted in a 40% reduction of calls to customer support. Middle Eastern companies know that digitalization is the way to the future. Business intelligence for the supply chain is becoming an integral part of various companies. But what is supply chain business intelligence? How does it help the companies, and which BI tools can be used to build a supply chain dashboard? What is Supply Chain Analytics? Supply chain analytics is the analysis of the individual elements of the supply chain that work together to help the business achieve its goals. Procurement, inventory, warehouse, order management, shipping, and deliveries are the elements of the supply chain. Understanding how every element contributes to keeping the supply chain running will help businesses overcome roadblocks and prevent delays. While there are various software applications to manage individual elements, companies need to bring it all together on a single platform/dashboard. This makes it easier to identify the correlations and come up with the necessary solutions. Types of Supply Chain Analytics The following are the four major types of supply chain analytics that help enterprises improve the efficiency of their business operations, streamline logistics, and save time and money without compromising quality. Key challenges that Supply chain analytics solution solves: Actionable Advice for Data-Driven Leaders Struggling to reap the right kind of insights from your business data? Get expert tips, latest trends, insights, case studies, recommendations and more in your inbox. How Do Companies Use Supply Chain Analytics? Companies use analytics to process and analyze the data generated at different points in the supply chain. The logistics dashboard empowers companies to stay up to date and get real-time information about their supply chain processes. It gives them the information to make last-minute changes and make decisions based on historical and real-time information. Managing local, national, and global supply chains is simpler when using supply chain analytics. How Can Supply Chain Analytics Transform a Business? Businesses need to invest in building supply chain dashboards to make the most of data analytics. Since companies don’t often have in-house teams to manage business intelligence, they hire offshore solution providers to create the BI dashboards. Many AI service providers recommend Power BI for supply chain analytics. Power BI is a Microsoft product that helps build business intelligence dashboards for various business requirements. Power BI experts help business enterprises use supply chain analytics to transform their business in the following ways: Streamline Inventory and Warehouse Management Accurate forecasting can reduce the uncertainties in inventory and warehouse management. Analyzing customer preferences, purchase history, market trends, and the inventory at different distribution centers will help businesses plan the stock in their inventory to keep up with the customers’ requirements. It is one of the most vital supply chain management techniques. Increase Sales Knowing which products have a higher demand and anticipating the changes in the market conditions will increase sales for the business. Supply chain analytics gives the management the necessary insights about the demand and supply ratio for their products. Releasing products into the market at the right time will give the business a better chance to capture the customer base. Improve Quality Standards The quality standards here pertain to the logistics and supply chain processes. For example, the Power BI logistics dashboard will make it easy to identify the gaps in the supply chain that are causing disruptions in procurement or deliveries. By rectifying the gaps, the business increases the quality standards of the process and gets higher returns. Data Utilization How a business uses the supply chain dataset determines whether it can achieve its goals or not. Big data solutions facilitate businesses to better understand the changing demands in the market. Not only does supply chain analytics use historical data, but it also processes real-time information from multiple sources to increase the accuracy of the forecasts/predictive insights. Supply chain analytics makes businesses proactive instead of reactive. How is Power BI used in Supply Chain Management? Power BI is a popular business intelligence tool used by enterprises of all sizes and volumes. Multiple dashboards can be created for each department to provide employees access to the centralized data sets and the derived insights. Supply chain analytics using Power BI improves functional efficiency and aligns the processes

Leveraging Business Intelligence in Retail Industry: Benefits and Getting Started

The business intelligence market is expected to grow with a CAGR of 8.7% and hit the 43.03 bn USD mark by 2028. Further, a recent survey suggests that 58% of companies consider business intelligence crucial for retail and wholesale sectors. Technological innovation is happening faster than ever and digital transformation is sending ripples across all the industries. As data analytics and business intelligence overtake the hunches and guesswork, the disparate and fragmented industries, such as retail, are looking at a major makeover. A recent feature in Forbes talks about customers becoming increasingly conscious in terms of making purchases and how important it has become to deliver exceptional services alongside great products. This has led to the widespread adoption of smart analytics platforms that offer business value across the most crucial 4 verticals, as shown below: The smart analytics tools allow retail business owners to dig deep into their customer data and uncover hidden insights about service, support, customer journeys, and brand expectations. The software solutions allow them to streamline their business offerings in a customer-centric manner and monitor the results of all such efforts. We discuss how business intelligence, such as interactive data visualization software, can offer retailing insights to steer your business towards growth. How would the retail industry use business intelligence and what is the best way to leverage it for boosting your business? Below, we explore these problem statements at length. Why Business Intelligence for Retail and eCommerce? Business intelligence allows you to make the most critical business decisions in a data-driven manner. You can dig deep into the customer data and find out what issues or concerns they have regarding your products. This way, you can improve your products and services to deliver delightful customer experiences. The best way to leverage business intelligence in retail is via software tools. Power BI is an excellent data visualization software that can dig deep into the customer, market, organizational, and business data to discover the most compelling retail visuals. The data generated from them are interactive in nature and highly secure, so you don’t have to worry about the safety and security of your data resources. You can connect these software tools to multiple data sources and tap into all your customer segments with its interactive and intuitive retail dashboards. What makes the entire endeavor so amazing is the fact that you can generate data-intensive reports from a combination of dashboards with different kinds of visualizations that are relevant to particular business areas. So, business intelligence has all the arms in its arsenal to drive a critical transformation in a retail business scenario via data visualization and business intelligence. Shown below, is how the entire process comes out to be: While the infographic is highly engaging and granular, it can be a bit overwhelming, especially for beginners who are just taking the first steps towards digital transformation and business intelligence. Hence, we explore the various benefits of using business intelligence for retail in the next section. Business Intelligence in Retail Industry: Exploring Benefits and Functionalities Business intelligence finds many applications in retail, ranging from learning about your customers to employees. Using BI tools, you can identify the major issues that are ailing your supply chain efficiency and resolve them. Further, BI tools offer smart data visualization to help you make the most of your organizational data. 1. Knowing Your Customers: Inside Out Digital shoppers are smart, more perceptive, and look beyond the reward points and discounts when it comes to customer service and experiences. Retail analytics dashboards help you gain visibility into customer insights and purchase patterns. You can leverage the predictive analytics and identify their shopping predictions to scale effectively alongside your customer demands. You can identify, adapt, and deliver across the ever-evolving needs of your customers, and that too across all channels. As you have a 360-degree view of your customers’ expectations and requirements, you can deliver across all of them, thereby ensuring that you streamline the entire customer journey instead of standalone touchpoints. You can personalize your customer interactions on every channel and deliver proactive customer service and support in an omnichannel manner. Business intelligence tools allow you to use hundreds of data connectors for combining Petabytes of data from external and internal data sources. Hence, you can have data-rich and cohesive customer insights that are reliable as well as intuitive. 2. Empowering Your Employees: The Right Mix of Human and Automation Your employees are your core strength no matter what level of automation you have in your organization, or what size your retail setup is. Hence, it is important to empower your employees with the right tools for collaboration, data analytics, customer intelligence, and business operations. All these retail insights are data-rich and actionable. So, your management or analysts don’t have to spend hours making sense of the huge blocks of data they have. They can easily figure out the next course of action with highly intuitive retail KPIs dashboards. They can easily export and share this data in various formats for real-time collaboration and presentation to take business decisions in an agile manner. What makes the entire process so awesome is the fact that the insights can be implemented without any doubt, as they are stemming from exhaustive data processing and not from any third-party market research data. Further, your employees have 360-degree customer profiles that have all the contextual, behavioral, and interaction information they might need to form a wholesome opinion about a new strategy or marketing decision. 3. Smart Supply Chains: Resilient and Efficient The retail industry is inseparable from supply chains that are inherently inefficient with data silos and fragmented components. Using business intelligence in retail, you can also steer your supply chains towards transformation. You can get the right product at the right price and deliver the same to the right customer at the right time without succumbing to the inefficiencies of the supply chains. Data analytics empowers the supply chains by incorporating different elements, such as IoT, automation,

Power BI HR Analytics Dashboard: Simplify HR Processes

Data analytics for HR helps streamline the human resource processes within the organization. The Power BI dashboard is commonly used to derive actionable insights to improve employee performance and retention rates. Let’s read more about the importance of HR analytics in an enterprise. The HR (Human Resource) department is the heart of every organization. From recruitment to compensation to performance appraisal and employee wellbeing, the HR department plays several roles in the enterprise. The HR acts as a mediator or a bridge between the employees and the management or enterprise. It’s no surprise that the HR department is already burdened with work. Providing them access to the latest technology and means to derive insights in real-time will help reduce the workload and create a healthy environment throughout the organization. HR analytics or people analytics is the key to helping the HR department provide a better working experience for the employees. Unlike other analytics, HR analytics doesn’t collect data about employee performance. It gathers data about the HR processes and the work environment so that the processes can be made more efficient to keep employees happy and productive. Issues such as high employee turnover rate, decreased productivity, employee grievances, etc., are the focus of HR analytics. What is HR Analytics? Human Resource or HR analytics is where analytical processes are applied to human capital in the business to improve outcomes and enhance critical talent. The analytics aims to provide in-depth insights into the HR processes to increase employee retention, performance, and productivity. The Covid-19 pandemic has affected the Middle East market along with the rest of the world. A report published in Jan 2021 showed that around half of the employees wanted to change jobs. While some responders said that flexible working and job security were their primary factors, 45% admitted that a higher salary was their aim. The employees in Gulf and UAE regions saw an increase and decrease in salary. While the increase was to retain top-level professional employees, the pay cuts were due to the pandemic and resorted after the market conditions improved. Around 64% of the employers in the Gulf said they would be hiring additional staff in 2021 and 2022. So how does the HR department make these decisions in volatile market conditions? They rely on HR analytics to understand the existing situation and come up with a new one. A survey report by CIPD showed that 82% of the respondents were already using HR analytics in the Middle East. Almost 72% of them responded that they will continue to invest the same amount or increase the investment in HR analytics. Middle Eastern organizations are actively upgrading the legacy systems and adopting the latest technology to provide employees with more growth opportunities. HR analytics will continue to play a vital role in helping organizations design robust and agile end-to-end HR processes. How to Get Started with HR Analytics? Data analytics in HR helps build the data-driven model to make decisions based on actionable insights in real-time. Implementing HR analytics requires proper planning and continuous monitoring to ensure that the analysis reports are accurate. Have a Data Management Plan How do you plan to manage the data within the organization? Start by creating a data governance program and define policies to collect, clean, process, and store data. Then you need to align the data definitions with analytical processes and focus on the four main key areas of human resources- recruitment, absenteeism, turnover, and retention. Choose the Reporting Software Which reporting and visualization software do you want to use to derive analytics? For example, Power BI is popular software for HR analytics and is used by many businesses from around the world. Build the Dashboard You also need to determine whether you have the necessary talent to run analytics or if you need the assistance of a Power BI consulting company. Many organizations in the UAE hire offshore solution providers to set up the HR analytical dashboard. The metrics you choose for the dashboard should align with the KPIs of your business and achieve short-term, midterm, and long-term goals. Run a Pilot Test You don’t need to invest heavily in HR analysis from the very first day. Start small by focusing on minimum metrics and run a pilot test to see how the insights are helping in making faster and better decisions. Gradually, you can expand the dashboard and hire HR analysts to manage the processes. Actionable Advice for Data-Driven Leaders Struggling to reap the right kind of insights from your business data? Get expert tips, latest trends, insights, case studies, recommendations and more in your inbox. Work on Capacity Building HR analysis reports are used to improve the processes and capacity of your business. Focus on one target group first before implementing the changes throughout the enterprise. Starting with the capacity building of HR Business Partners is recommended as they are the ones who are in constant contact with your customers. Consider Data Privacy and Security Dealing with employee data means you have to be extra careful about data privacy. Your employees need to know that their data privacy rights won’t be compromised to run HR analytics. Set up policies to find a balance between both. What are the Benefits of HR Analytics? The HR analytics dashboards help the business adopt a strategic approach to growth and development. How Power BI Consultants Can Help You Overcome the Biggest HR Analytics Challenges? Though the HR analytics dashboard offers numerous benefits to the organization, the process is not without challenges and complications. How you overcome the roadblocks determines the success of your enterprise. Power BI consultants can help the HR team find a comprehensive solution for the challenges and create HR analysis dashboards to derive real-time insights. A Gap in Talent Pool As we previously discussed, the lack of data analysts within the enterprise can make it hard to use technology and derive insights for the HR team. This problem can be solved by hiring offshore consultants. Bad Data The accuracy of the reports depends

Is BI a Revolution in the Banking Industry?

Business intelligence is no longer a strange phenomenon in the banking industry. It is a revolution that’s changing how banks perceive data and analytics. We’ll discuss the role of BI in banks in the modern-day scenario. Technological innovations are the key to being relevant in this fast-changing world. The banking industry is not an exception to this rule. From following traditional bookkeeping methods to computerizing the transactions, we’ve noticed many changes in the banking sector. Another such development is the use of analytical tools to streamline internal operations and enhance customer experience. Even the banking industry has competition as more banks are going multinational and opening new branches around the world. Collecting data, creating a centralized database, and processing huge volumes of data requires much more than legacy systems and spreadsheets like MS Excel. Business intelligence has successfully entered the banking, insurance, and financial sector. Banking analytical solutions can help employees, management, and the leadership have more control over day-to-day operations and provide better services to their customers. BI is undoubtedly a revolution in the banking industry, and here’s how. What Is Business Intelligence? Before we talk about how BI is changing banks and financial establishments, let’s first understand what business intelligence is and why it is important. Business intelligence is a set of technologies, processes, architectures that help collect, clean, and convert raw data into meaningful and actionable insights. BI is a suite of software applications and services used for transforming data into intelligence. Business intelligence impacts the operational, strategic, and tactical decisions of an establishment. BI tools are used to collect, clean, format, process, analyze, and present data in real-time. BI uses historical and real-time data to derive insights and generate reports. Employees can run queries by setting parameters to get accurate responses from the tools. Business intelligence is important to measure KPIs, set benchmarks, identify market trends, overcome challenges, and make data-driven decisions. Applications such as Power BI, Tableau, Qlik, etc., are some well-known business intelligence tools used by businesses from different industries. Power BI is the most preferred tool in the banking industry. What Is Business Analytics in Banking? Business analytics help in understanding the bank’s data based on statistical models and quantitative methods. Analytics can be used in various ways in the banking industry. The core reason to use business analytics is to answer questions like: Business analytics is a part of BI. How Is Business Intelligence Used in Banking? Consumer Trend Forecasting Knowing what the customers want is important to achieve the bank’s goals and generate profits. Banks offer a range of financial services for individuals and business entities. From operating a savings account to funds management, loans, credit cards, and insurance services, the banking industry deals with everything related to money management and control. Business intelligence helps in analyzing the huge volumes of data generated every day to identify the trends in customers’ demands/ requirements. Is there a decrease in home loan applications? Are more customers investing in a certain mutual funds scheme? Finding answers to these questions will help the management make the necessary changes to their financial products and services. Better Marketing Effectiveness Understanding your customers is a good way to increase your customer base and ensure brand loyalty. The banking industry has become a competitive field. You need to reach out to the target audience with offers that’ll surely make them consider you as a first choice. But how do you know what the market wants? BI in banking helps use customer data and data analytical tools to derive insights about each target base. It is not essential to spend money on ads that may or may not be effective. You can create ads for each target group with the confidence of knowing what they want. The bank can generate more returns with less investment, identify the weak points in the existing marketing strategies and correct them in time. Data and Cybersecurity According to a report shared by Security Magazine, the banking industry saw a 1318% increase in ransomware attacks in 2021. Banking data of individuals, corporate entities, and non-profit organizations are highly confidential information. While this data can be obtained through several malpractices like hacking and phishing, a cyber attack on a bank’s database gives criminals access to valuable information in bulk. Business intelligence tools play a role in monitoring the network traffic and can alert you in case of irregularities. The data collected and analyzed by BI tools gives security experts the necessary information to identify hot spots and improve the security layers at each level. Retain Customers Customer retention is necessary to maintain a healthy customer base. A bank needs to have customers who’ve been with them for years and will continue to be. Providing personalized services and ensuring quality customer experience promotes customer retention. BI tools can be used to identify customers who are more likely to impact their business with the bank or move to a competitor. You can also understand the reasons behind this trend and find ways to prevent it from happening. CEOs, CFOs, and other chief executives can run analytics on historical and real-time data to understand the patterns and come up with a solution. Calculating Credit Risk Should you approve the loan application of a customer? What is the risk associated with it? Banks already have a system to process credit requests and approve/ reject applications based on it. However, changing times require advanced systems. You may need to consider more risk factors, especially when the customer is a business entity and the amount is millions. Banking business analytics is used to process customer data from multiple sources. It helps analyze spending habits, income stability, and the probability of fraud before a loan application is approved. This lowers the credit risk for a bank and reduces defaulters. Compliance Assurance The banking industry has to adhere to the various regulations set up by the national and global bureaus that help in establishing anti-money laundering norms, etc. Banks have to regularly send reports and updates

Power BI for Retail Industry: Dominate the Sector

With an increase in competition in the retail sector, it has become extremely important for every retail company to understand advanced technology stack, people and data. Power BI is one such technological advancement that allows retail businesses to leverage its functionality for data visualizations to improve their profitability and efficiency while acting on real-time insights. In fact, the usage of any business intelligence tool is considered a crucial key to managing a company’s data in this digital age. It is used to generate reports, surface insights and connect to a wide range of information for better understanding. The reports offer visualization of the data that boosts the sales for the business by facilitating better planning and strategizing. Today, we will discuss the applications of Power BI for retail and what makes it one of the most efficient retail reporting tools. Benefits of Power BI in the Retail Industry Since the outbreak of the pandemic, the retail industry is slammed with the challenge of uncertainties. Moreover, the growth of digitalization has enhanced customer expectations. As per a survey, the e-retail industry in the Gulf Cooperation Council (GCC) region was predicted to grow at the rate of 12.2 percent of the offline retail in the year 2025 (before the COVID-19 pandemic). The forecasted penetration rate grew to approximately 16.3 percent after the pandemic. Therefore, customer demands follow a different pattern in today’s digital era. Along with the products or services, the customers are also given equal importance in today’s economy. Every business and retail industry is looking forward to providing their customers with quick satisfaction and a smooth experience. The retail industry is suggested to analyze and collect the data for coping with the changing customer expectations and rising demands. With the applications of Power BI, the industry can expect the transformation of raw data into actionable retailing insights. It can offer every business a 360-degree view of their entire industry at a glance. Moreover, the efficiency of the Power BI retail dashboard helps understand the selling and buying habits of the customer. Thus proving to be the top retail business intelligence tool in the e-retail market. Let us look into the major advantages of using Power BI in retail: Since it is clear how Power BI for retail can prove to be beneficial, let us now understand its technicalities. How Does the Power BI Sales Dashboard Work? As we discussed earlier, the business intelligence tool by Microsoft helps to analyze data present in different sources and build dashboards and reports based on the data. Top-level management effectively uses Power BI’s dashboard for retail operations as it is capable of generating an alert once it notices low stock. It helps to create accurate reports on the profitability of the products. Apart from endless uses of the Power BI retail dashboard, the report generated by the BI tool helps to analyze the cash tied to the existing stocks. The industry can avail the advantage of getting the data source with the help of Power BI. Companies can keep track of the inventory status, changes in customers’ shopping trends and the value that any supplier holds using the BI tool. For example, a Customer Analysis Dashboard will help evaluate profit and sales while generating valuable insights based on product turnover-related, dynamic customer behaviors. As an illustration, retail companies in the Middle East and North Africa (MENA) could analyze a decrease in in-store shopping following the COVID-19 pandemic. Further, noticing an increase in shopping via the PC. A survey conducted in 2020 supported the data analysis by predicting the growth curve of the e-commerce industry in the Middle East region to accelerate to five years in about five months. How Would the Retail Industry Use Business Intelligence? The powerful dynamic of business intelligence can be used in many ways by the retail industry. Some of the most useful ways are as mentioned below: Following up with Changing Trends Keeping up with the latest customer trends has become seamless with the help of Power BI. Now every industry can use Power BI to analyze big data that projects the pattern of change in the customer’s purchasing behavior. Using the retail visuals can help the industry monitor, plan and assess the effectiveness of various promotional activities. It can also draw a report on how a particular group of customers reacts to specific marketing campaigns. Moreover, the Power BI can collect social media data while analyzing it to measure the high engagement level, track the demographics, and assess the influencing behavior while understanding the buying patterns. With the help of the retail analytics dashboards, you can boost the efficiency of the supply chain while meeting your customers’ demands. It can also help meet the seasonal demand while enhancing the forecasting ability. Get the Omnichannel Experience The multi-channel retail would get replaced with the help of a more engaging omnichannel experience. Power BI helps to unify the customer in every action and touchpoint. It helps to treat the single-channel interaction for a more delightful customer experience. Power BI helps to aggregate the data from various offline and online sources with the help of a visualization tool that helps predict user behavior. It also helps get a unified picture of the expectations and demands of the customer. Assessment through the budget is only possible with the help of Power BI. It helps to understand the different areas of intelligent plans, cost-cutting, predictive analysis and floor optimization to balance the demand and supply of the perishable results. Assists All Team Members The data analysts can dig deeper with the help of the advanced features of Power BI, including map visualization. It also helps them unfold the platform’s predictive analysis potential by using R scripts. The team helps the executive keep an eye on the critical parameters while helping them with an all-encompassing and comprehensive report generated via Power BI sales dashboards. It can help them to access a high-level picture of the situation within less time. The top-level management is

Why BI is important for C-Level Executives in BFSI

Business intelligence is used to derive insights from data and helps in decision making. Make the most of big data to understand customers and improve their experience with the financial company. Let’s discuss how C-level executives can use BI tools to achieve their goals. The Banking, Financial Services, and Insurance industry has changed over the years and is now leaning towards the customer-centric model. The increase in competition, the unexpected losses, and the changing trends in the market are some reasons for this development. The C-suite executives have a huge role to play in streamlining the banking operations, increasing revenue, and enhancing customer experience as they are the decision-makers in the establishment. Providing customers with a worthy experience has become essential for a financial company to establish itself and become a popular name. However, achieving customer satisfaction is not possible without knowing what customers want. This knowledge comes from the data collected by the institutions. That said, raw data is of no use unless it is cleaned, processed, and analyzed using data analytics tools. In short, financial institutions need advanced tools to adopt the data-driven model. The tools and the processes come under business intelligence. Financial establishments mostly hire the services of offshore BI consultants to build the data-driven model and implement the necessary tools like Power BI for data analytics and reporting. A financial establishment with noteworthy customer experience is proof that it has everything under control and is at the top of the game. What is Business Intelligence? Business Intelligence is a technology-based process used by business organizations to collect, clean, store, streamline, and analyze large volumes of data in real-time. Business intelligence delivers high-quality and accurate insights used to make business decisions. Data mining (collecting data from multiple sources), predictive analytics, and data visualizations (reporting) are an integral part of the business intelligence process. There are several BI tools in the market. For example, Microsoft Power BI and Tableau are well-known tools for business intelligence processes in various industries. The BFSI industry relies on Power BI for financial, operational, and marketing purposes. This certainly doesn’t mean that BI is only limited to the banking and finance sector. Let’s look at some of the benefits of using business intelligence in banking and financial companies. Benefits of BI Tools Why BI is Important for C-Level Executives in BFSI Business intelligence has a prominent role in customer experience. CEOs, CFOs, COOs, CTOs, etc., can use BI tools like Power BI for the following: Real-Time Reporting The executive leaders don’t need to wait days and weeks to access data reports. The reports are automatically generated in real-time and shared using the dashboard of the BI tool. They can export the reports to other applications and send them to team members, management, etc., whenever required. Why spend hours of your time creating reports when you can set up the process and let the software do the rest? Omnichannel Customer Insights Structured and unstructured data from multiple sources (social media, call recordings, emails, messages, surveys, feedback, etc.) is collected in a centralized database. This data is cleaned and analyzed to derive insights to get a complete picture of a customer (to build customer profiles). This helps create better financial products, plan marketing campaigns, and convert more leads into customers. The chief executives don’t have to rely on outdated reports or past experiences to determine the best way forward. They can use real-time reports to target the markets and capture a larger customer base than the competitors. Collaborations The C-suite executives have to work in tandem with teams from sales, marketing, and financial departments in the establishment. From setting up the budget for customer acquisition to allowing the sales and marketing teams to brainstorm and share information seamlessly, BI tools help create a healthy environment in the organization and promote collaborations between employees and stakeholders. Automate Customer Engagement The metrics and data thresholds of BI tools act as natural triggers for automation. You can establish workflows and campaign timelines and schedule customer meetings based on the analytics. When you contact a prospective customer at the right time in the right way, the results will be favorable for your organization. Business intelligence gives you the necessary information to identify the best course of action and helps automate the processes. Predict Customer Demands It’s no surprise that customer demands change based on geographical location, market trends, and demographics. By predicting the changing conditions and demands, banks and insurance companies can offer financial products useful for customers and thus increase their market share. You can conduct surveys and use beta groups to study potential customers in new/ unknown markets. Root Cause Analytics Root cause analytics is where you identify the actual cause for a problem at hand. This is done by analyzing relevant information (historical and real-time) for the adverse condition you need to overcome. Business intelligence tools like Power BI can quickly process big data and generate data visualization (graphical) reports about the reasons for the problem/ adverse condition. Convince the Team One of the toughest tasks the chief executives face is to convince the topmost leadership and other chief executives about a campaign, an investment, or a decision. The reports generated by BI tools help present data clearly for the leaders to understand the potential of a project/ campaign and the expected ROI. Since the reports are generated using data analytics, it becomes easier to make decisions that impact the organization. Risk Mitigation Chief executives need to stay one step ahead and filter the leads to minimize the risk of attracting fraudulent customers. Identifying who/ which group is likely to commit financial fraud or misuse services will help banks cut down losses. Be it unpaid loans or vanishing customers, the financial establishments have to handle various types of frauds and find ways to overcome the losses. Integrating BI tools with data sources and existing apps will help in running automated analytics and sending alerts to the respective employees when there’s a possibility of a fraudulent transaction Better Customer