Mobile Business Intelligence empowers business

One of the main conditions for a successful business today is the correct work with data. Effective business activity largely depends on the speed of decision-making. It is possible to make an informed decision quickly due to certain data manipulations. That’s why it is important that the data is available in real time anytime and anywhere.

Mobile Business Intelligence involves the provision of data analytics and data analysis services to mobile, portable devices and remote users. The tool works in the same way as a standard BI software solution and allows users with limited computing capabilities to use the same functions and processes.

Modern companies are no longer limited to the walls of a physical office. Mobile and portable devices development has made it possible to organize an «office» anywhere: a cafe, an airport, another city or country. Businesses are becoming more agile. Mobile BI implementing is a logical step. Among other  things the purpose of such tool introducing is obtaining a competitive advantage.

Benefits of Mobile business intelligence

  1. Making effective business decisions

Mobile BI solutions are built to support mobile communication. It has built-in messaging functionality. Also, some tools are equipped with complex mechanisms that allow to transfer rich information content (voice, image, video). These features provide managers with the opportunity to collaborate and discuss during the analysis process, to receive complete information for making informed decisions.

  1. Access to data in real time

A valuable mobile BI benefit is having corporate information here and now. User capabilities are not limited to one computer. Data can be accessed on a personal mobile device anytime and anywhere. This access to information improves the overall performance of business operations.

  1. Customizable and structured analytics

Each company is an individual, that has its own preferences and requirements for data analysis (to the process, visualization, integration with other tools, etc.). Mobile BI solutions are built to be customized. With the ability to apply customizations, executives and other business users can effectively analyze data, draw conclusions, and come up with new solutions and insights.

Mobile BI applications usage is growing rapidly. Quick access to real-time information, flexibility, higher speed and productivity enable to grow the business, gain a competitive advantage and increase profits. Between 2021 and 2026, the Mobile Business Intelligence market is forecast to post a CAGR of 22.43%.

Business Intelligence is a tool for effective business performance

Business Intelligence is a set of methods and technologies for data collecting, processing and analyzing. BI connects business analytics, data visualization, data mining, infrastructure and data processing tools, technologies for making informed decisions. The tool allows to work with business activities data, obtain data on competitors, and determine market trends. This allows to make effective data-driven decision-making process, optimize all business processes, including customer experience and employee satisfaction improvement, ensure smooth efficient operations and increase revenue. Let’s take a look at exactly how Business Intelligence can help improve a business.

  1. Data driven decision making

Business Intelligence enables an efficient decision-making process by transforming disparate information into ready for analytics data. Access to up-to-date corporate information provides a prompt response to any events. Customer Relationship Management (CRM) solutions bridge the gap between staff and managers.

  1. Customer needs analysis

Along with active changes in the market, customers’ needs and interests are changing. Each client is looking for the best way to solve their problems. This influenced the growth in demand for embedded BI tools, in particular CRM. This system allows to study the client’s interaction process with a particular brand in real time, as well as to determine the best way to interact with a particular client. Analytical data also makes it easy to segment customers depending on their life cycle, set up individual interaction methods. This approach ensures optimal resources usage to attract new customers and maintain the current customer base. Moreover, Customer Relationship Management (CRM) solutions bridge the gap between staff and leaders.

  1. Improvement of market analysis effectiveness

Business Intelligence helps to get complete and up-to-date market information. Users have the opportunity to analyze data on shopping patterns, identify information about customers, their behavior, and predict market trends. This in turn contributes to more efficient planning of business activities.

  1. Effective business model

Working with all the data company owns, including marketing strategy, data on competitors, market, buying habits, and more allows to create a reliable and results-oriented business model.

  1. Sales strategy

To develop an individual sales strategy, it is important to study and understand information on sales volumes, annual turnover, competitors, trade policy, etc. BI tools used to study these indicators allow to plan lead cost, turnover, future growth, number of sales and develop an individual marketing plan.

  1. ROI on Marketing

Currently companies use many channels and ways to promote their product or service. BI tools provide an opportunity to calculate the ROI of a marketing initiative (email marketing, promotion in social networks, applications, Google Ads campaigns etc.) and determine the most effective marketing solutions and strategies.

  1. Mobile business intelligence

Getting up-to-date information is an important component of any modern business. Access to real-time data provides an opportunity to gain a competitive advantage. A fully integrated mobile business intelligence solution gives an access to the business information you need to make strategic decisions.

Business Intelligence Challenges in 2022

The huge data amount that modern companies own provides new opportunities for their development. But it is also a source of additional problems. The main purpose of Business Intelligence is to provide processes for collecting, processing and analyzing data. However, there are some issues that make it difficult for BI to be efficient, effective, and useful. Let’s take a look at the main Business Intelligence challenges.

  1. The problem of data integration from different source systems

The number of data sources is increasing. For a complete and correct analysis, companies need to collect data from various sources: databases, big data platforms, internal and web applications.  A fairly common option is to use a data warehouse as a central repository for business intelligence data. Using data virtualization or BI tools to integrate data without putting it in a database system is a more flexible option, but too difficult process.

  1. Data quality

The accuracy of BI applications is directly dependent on the data they are based on. The start of any BI initiatives assumes that the user has access to high quality data. However, many companies are in the pursuit of collecting as much data as possible. That’s why they don’t pay attention to the quality of the data. Moreover, they believe that problems can be solved after the data is received. The reason for this position may be users’ knowledge lack about the data management importance and necessity. It makes sense to develop a strategy for collecting the right data and a data management plan before BI technologies deployment.

  1. Data Silos with conflicting information

A common BI problem is siloed systems. Successful business intelligence requires data completeness. However, different levels of access and security settings complicate the process of necessary analytical data obtention. To achieve the desired result, it is necessary to disintegrate silos and harmonize the data. Contradictory disparate data can lead to different versions of the truth. Then business users get different results for KPIs and other indicators that are the same in different systems. To avoid this situation, it makes sense to start with some level of data modeling and precise definitions for each KPI.

  1. End-user training

It is important for the end-user to understand the purpose of introducing and using the innovation. Company executives and managers should also be actively involved in effective learning and change management initiatives related to BI projects. For a wider and faster changes implementation, it is worth developing a short and understandable user training program.

  1. Managing the process of using BI self-service tools

An uncontrolled deployment of self-service BI can lead to a chaotic data environment with disparate repositories and conflicting insights. BI tools are regularly updated. Business analysts should interact with end-users to better understand their needs and develop strategies for delivering relevant data and dashboards using off-the-shelf functionality.

  1. Low level of BI tools implementation

End-users quite often choose the simplest option and use Excel or SaaS. It is important to develop a good user scenario that will demonstrate immediate business benefits and encourage employees to use the new system before starting to deploy BI technologies.

  1. Dashboard design

Difficulties in understanding information can occur due to failures in data visualization. Dashboard and analysis can be useful when end-users can easily explore the information provided. However, the focus on data acquisition and the analytics process takes the design issue into the background. It is worth involving a UX designer to create a simple and understandable visual interface.

BI tools to improve business results

Most businesses consider Business Intelligence to be a critical tool for their current and future business strategies. According to Forbes, 54% of enterprises are adherents of this opinion. BI tools help transform company-owned data into ready analytical formats (reports, dashboards, etc.). The range of issues that business analytics helps to solve is very wide (product prioritization, supply chain optimization, workflow optimization, etc.). All BI products are designed primarily for making informed and effective decisions to optimize business activities in general.

Consider the main tools of business intelligence

SAP BusinessObjects is a flexible, scalable information infrastructure for discovering, exploring, and presenting data to make better business decisions. The key features of this system are:

Datapine is a one-stop platform for data visualization and business intelligence. The tool allows data scientists and other business users to use different data sources, perform advanced data analysis, create intuitive business dashboards, get answers and draw the right conclusions.

Microstrategy is a modern business intelligence software (integrated reporting, analytics and monitoring). The tool combines fast logical and factual capabilities to provide real-time assessment with third-party data analysis. Microstrategy also allows to process unstructured textual information, that can be further analyzed by specialists using a text analytics platform.

Qlik Sense is a data visualization, exploration and monitoring tool, business intelligence platform with in-memory associative search with built-in ETL tools. The wide functionality of the tool allows to collect data from disparate sources into a single information system. The associative data model provides the ability to explore data in any direction, understand the relationships of data and see all the relationships between them. These and other Qlik Sense features have made it one of the best and most popular BI tools. DataLabs develops custom BI solutions based on Qlik, focused on effective business management. Detailed information can be found here.

Sisense is a software BI tool that combines dynamic and powerful text analysis features. This allows users to transform text into valuable insights.

Zoho Analytics is a platform for self-service BI and data analysis, as well as internal and external information discovery. The tool allows to download, synchronize data from different sources (spreadsheets, applications, etc.), create and share dashboards and reports. Zoho Analytics offers connectors for rational databases and NoSQL databases and connects to cloud databases.

Microsoft Power BI is a set of data analysis services that allow to turn unrelated enterprise data sources (databases, data from cloud sources, the Internet, text files, Excel files) into reports, presentations and business plans. Power BI includes: Power BI Desktop – data models and reports creating); Online service Power BI (SaaS) – reports publication; Power BI Mobile – reports viewing on mobile devices and tablets.

Tableau is a BI tool for data discovery and visualization. The tool provides an easy process for analyzing, visualizing and sharing data without the help of IT specialists. Tableau belongs to the «self-service» category, providing all the opportunities for users to work independently.

Oracle BI is a business intelligence software product (interactive and published reports, KPI monitoring, business process monitoring). The platform supports different data sources and combines data from these sources in one report.

Business Intelligence and Business Analytics Trends in 2022

Data is an indispensable tool for modern business. It is used everywhere in business: from supporting the decision-making process itself to upgrade and improve products and services. 2021 has been a year of intriguing advancements in Business Intelligence and data analytics. The goal was to provide companies with a custom solution based on different technological approaches to make the most of their data. Given the dynamic pace of development in this area, new solutions can be expected in 2022. Consider the main trends in the development of Business Intelligence and data analysis.

  1. Data Factory and Hybrid Cloud

The Data Fabric is a cohesive, conceptual information management architecture that provides complete and flexible access to work with it. Data factories feature is the use of the approach and tools of Artificial Intelligence, Big Data and machine learning in order to organize optimal data management algorithms.

The latest development from Qlik is an example of such a concept. Qlik Forts is designed to connect all data regardless of its location in the cloud. Companies using a variety of private and public cloud platforms have the ability to easily connect and leverage all of the data for an efficient workflow. Moreover, the data is available for analysis to the user from anywhere in the world. In 2022, the development and bringing of analytical solutions to a new level.

  1. Automation and Machine Learning

Nowadays, most of the commonly used machine learning algorithms perform their functions well and smoothly. Specialists, in turn, are trying to improve developments and make them even smaller, faster and more efficient. The next year will be devoted to platforms and tools development that can be used by any user to automate any task.

  1. Small data

To solve the scaling problem mentioned in the previous point, it’s worth starting by changing AI and machine learning goal. It is advisable to process only the most important data, in other words, go to small data. However, this does not mean that big data is losing its value – it will always be needed. We can already see the success of implementing the «small data» approach in self-driving cars to quickly respond to potential road accidents. In 2022, we can expect new ideas emergence with the effective use of small data.

  1. From SaaS to iPaaS

One of the trends next year will be SaaS (software as a service). However, in 2022 there will be some changes, namely iPaaS. The tool is a cloud-based solution with the ability to easily scale and integrate large data amounts. Gartner defines iPaaS as a cloud services set that enable the development, execution and maintenance of integration flows that connect any combination of on-premises and cloud services, processes, applications, and data within one or more organizations. The goal of every company is to avoid data loss and information silos across departments and platforms. Therefore, a breakthrough in this area is expected next year.

  1. Planning and forecasting

Back in 2020, the predictive and prescriptive analytics market was projected to grow by 20% over 5 years. Now analytics is becoming more accessible to users. With the help of Qlik BI platforms, it is possible to easily integrate predictive analytics into CRM, ERP, etc. In 2022 and beyond, this area will actively develop.

  1. Information literacy

The final item on the trend list is information literacy. Knowledge is essential for the implementation and correct use of all technologies and innovations. Otherwise, all progress will be meaningless. Modern companies that strive for dynamic development should think about quality training for their team. End users require particular attention, as they often make data-driven decisions.

Business Intelligence vs Business Analytics

Business Intelligence and Business Analytics are the indispensable and most common tools of modern business to optimize workflows. To understand how each tool can benefit, let’s figure out the definitions.

Business Intelligence is the process of collecting, storing and examining data owned by a company to ensure smooth operations. BI includes various tools and software: spreadsheets, reporting system, monitoring software, data mining software, event management, online processing, dashboard development, etc. BI provides the ability to interpret big data, identify new opportunities and implement new development strategies. The ability to combine internal and external data is the BI advantage. This provides a clear current situation vision and understanding, that cannot be obtained using single data. Incorporating BI into the workflow helps organizations understand the business, market, customer needs and behavior.

Business Analytics is a statistical technology using quantitative methods for obtaining information, forecasting defects, and developing strategies. BA tools: predictive analysis, forecasting analysis, data aggregation, association and sequences identification, correlation analysis, factor analysis, data visualization, growth analysis, optimization, etc. BA usage involves the involvement of data processing specialists, as well as an additional specialized training. The decision-making process with BA occurs through numerical analysis methods (predictive modeling, analytical modeling, explanatory modeling).

What is the difference between Business Intelligence and Business Analytics?

  1. The main focus of BI is the analysis of historical and current data. BI provides a process for analyzing / comparing past events, the current situation and business development over a certain period. Using this tool it is possible to find the cause of the problem and determine the necessary actions to fix it. The main focus of BA is predicting future results. Using this tool it is possible to determine the consequences of an unresolved problem in the future, possible strategies and predict the results.
  2. BI works with past and current data to determine business needs. BA works only with past data to predict business needs, customer needs and drive productivity.
  3. The task of BI is to provide a vision of current business operations, information on current trends and customer interests. The task of BA is to provide information on changes in business operations, increased productivity, future customer needs.
  4. Basic BI tools: Qlik Sense, SAP Business Objects, TIBCO, PowerBI, etc. BA tools: Word processing, Google documents, MS Office tools, MS Visio, spreadsheets, etc.
  5. BI is a tool mainly for large companies whose goal is to ensure smooth running of business. BA is a tool for small companies to develop business, improve efficiency and achieve goals.
  6. BI uses more User Interface Dashboards for analysis and carrying out operations, BA uses more tools and software applications.
  7. BI methods and technologies for data analysis: reporting, real-time analytics, dashboards, online analytical processing, etc. BA methods: predictive modeling, data modeling, requirements modeling, SWOT analysis, etc.

BI and BA perform different tasks and roles in the business optimization process. However, both tools are an important and integral part of operational activities for better understanding the business, ensuring an efficient decision-making process, optimizing business processes, predicting trends and gaining a competitive advantage.

The influence of BI on business performance

Until recently, BI applications were mainly used only by IT professionals. With the technology development, Business Intelligence has become the main tool for many business users from various fields of activity.

The main task of Business Intelligence is to extract important facts from structured and unstructured data, transform it into coherent information that allows to make effective business decisions, increase productivity and optimize the operational activities of the organization.

Business Intelligence is a workflow that, by scanning data and extracting facts from it, helps business owners, managers and other business users to see a clear picture of the current situation, analyze and develop an appropriate action plan. With the help of this tool, companies are able to collect information from internal business structures and external sources, that makes it possible to improve the internal business structure, identify market trends, and identify problem areas.

The wide information resources provided by business analytics enable companies to achieve their goals faster. Any interaction with customers (voice messages, testimonials, chatting or email communication) can be carefully analyzed to extract information about customer preferences, technical difficulties they face, their reactions to promotions, purchasing power, etc. Analysis contributes to the improvement of all business indicators.

A high-quality process of making effective business decisions is provided by Business Intelligence. The main business areas affected by Business Intelligence within the company:

  1. Increasing business productivity

The business analyst team is dedicated to extracting and interpreting data using BI applications. Thus, the company management can focus on the management of important resources and workforce. The result of this approach is financial and time costs improvement and business performance optimization.

  1. Extraction of critical information

BI provides business users with the ability to extract critical data by analyzing customer interactions and visualize them in a convenient and understandable way. The tool ensures that detailed and reliable reports are provided to all business users.

  1. Information availability

By incorporating Business Intelligence into the workflow, companies gain access to all the data they need to make decisions. Users can get such access at any time.

  1. Return on investment

The main BI advantages are the ability to reduce costs, increase revenue, and increase margins. It helps to improve ROI. BI also helps to improve indicators such as employee productivity, quality of decision making, customer satisfaction, business process efficiency, etc.

  1. Real-time reporting

A high-quality report based on reliable information provides the company’s management with a clear understanding and the ability to evaluate business processes. By providing reports on critical data (current and historical), as well as data on future trends, customer needs and preferences, companies are able to operate effectively.

Clear strategy defines success of digital transformation

In the past 10 years, digital transformation has been quite calm and slow. However, the pandemic has changed this trend by shedding light on the shortcomings of the enterprise technological infrastructure. This situation has forced decision-makers to prioritize IT and increase investment in digital solutions.

Digital transformation is the advanced technologies integration and implementation into business processes. This process is not limited to just hardware or software implementation. It involves profound changes and review of management methods, corporate culture and external communications. Increased employee productivity, high level of customer satisfaction, good reputation and efficient company operations are the result of digital transformation.

In the service industry, digital transformation plays an important role to understand customers and meet their expectations. The transformation process defines digital changes in value formation for products and services development, production, promotion, distribution and sale. Business users can use the generated data to improve customer service and efficiency. This, in turn, makes companies competitive.

The rise of digital innovation has pushed business leaders to implement transformation strategies to reach their target audiences and align their business proposition with customer needs. The right approach will ensure that you understand and build a successful digital transformation framework.

Let’s take a look at a few steps to successfully implement a digital transformation strategy:

Technology advances every day, forcing businesses to quickly adapt to any changes and update their business operations. To be successful and keep up with technological progress, you need to be aware of the possible results. It is important to predict, understand and analyze all changes after the proposed transformation, to understand necessary changes, their results and customer reactions to them.

After goals defining and results prediction it is necessary to select relevant technologies. It is important to understand here that digital transformation is not about mindless investment in advanced technologies. This process means the «right» technologies choosing to help business achieve goals.

Choosing a technology, it is important to answer the following questions:

  1. Does the chosen technology align with your digital transformation strategy and business proposal?
  2. Will the technology rectify operational processes deficiencies after implementation?

The technologies choice is followed by the technical part of the strategy, including the creation of a new digital platform and changes in the operating model.

Digital transformation affects all business areas, both external and internal. The right corporate culture implementing can be a stumbling block in this process. Communication is the key to create a healthy corporate culture. Communication and leaders’ involvement to explain the new vision of business processes, training and consultations allow each team member to quickly accept, understand innovations and be effective.

Digital transformation fundamentally affects business and requires a strategic approach. The technologies being deployed must expand core business capabilities and meet customer expectations. It is important to shift the focus to creating new services and products. To understand customer behavior, market trends, avoid possible losses, it is worth using data and analytics.

Digital transformation can be done easily and painlessly. A well-thought-out strategy and relevant technologies will help you quickly adapt to changes and meet the growing customer needs.

Business Intelligence improves customer service

Customer service is always of immediate interest, and it has a significant influence on business activity generally. With the advent of COVID-19 the whole world was convinced how important customer service is. Almost all offline business had to move activity into online and organize here an effective customer service process. Besides the enhanced online functionality, it required communication clarity and simplicity.

Many companies initially understood that the customer support in «such difficult time» would provide them with increased loyalty in the longer term. Now «pandemic disruption» continues, and business success directly depends on its client-focusedness, customer needs and interest knowledge. It is possible to meet these challenges with the help of BI.

The role of BI in business is invaluable. With the help of BI tools, it is possible to understand deeper: business, customers both their behavior and needs, to make reasoned decisions. By combining several information sources Business Intelligence allows to evaluate the current performance efficiency, identify patterns, define possible future problems and prevent them. According to the Gartner’s forecast BI will grow to $29,48 billion by 2022 and it proves again its value.

5 tasks that can be solved by Business Intelligence:

  1. The single source of truth creating

The modern business has many different information sources including ERP, CRM, website, social media etc. Business Intelligence collects data from all sources and visualizes it. In this case data consumer can easily see and analyze the full picture of customer interaction without manual data checking and collection.

  1. Real-time information receiving

To analyze and make decisions in hindsight is ineffectively. It has an impact on customer relationship, competitiveness and relevance. BI tools provide real-time analytics. With the help of advanced technologies data is transferred from different channels and platforms directly on dashboard. It allows to make rapidly well-founded conclusions and respond to customer behavior changes.

  1. Reasoned decisions making

The main BI task is to eliminate guesswork and enable data-driven decision making. Dashboard data allows to analyze and identify ineffective channels, for example by customer conversions. It allows to perform a change to the strategy, forward the budget and get the best result.

  1. Omnichannel

Customers expect their interactions with a particular company to be known to all employees. Addressing to support team client would like to explain his problem once. Aspect defined that 89% of customers are dissatisfied if they need to repeat information again and again. In this scenario Business Intelligence provides all channels view that allows to monitor the full history of the customer.

  1. Churn reducing

Churn rate is one of the main customer service and business effectiveness indicators. Customer retention is always cheaper than new customers searching and attraction. BI dashboards help define in time problem parts that allows to make changes rapidly for customer retention. For example, increasing the time to solve problems, customer support team restricting or training etc.

These are just a few examples of how BI can improve customer service. Depending on business specification and individual needs BI abilities are unlimited. For more information about Business Intelligence possibilities and benefits please contact DataLabs.   

Innovations that have transformed Business Intelligence

One of the most common questions that business owners ask themselves is «How to be competitive and outperform competitors?» A couple of years back the main characteristics for getting a competitive position were price, design and advertising. Now they are not the only ones. Understanding the client, his needs, willingness and ability to pay are the main characteristics that determine a competitive advantage. Data and BI are too important here because they can help to reply to these questions. The 3rd BI generation release gave a possibility to afford analytics tools to every business user and bring to the light the full data value. The current business intelligence scenario is driven by innovations.

Let’s consider some of them:

  1. Technology shift

Let’s come back to 2000’s. The appearing of a big number of users promoted the appearing of a big data amount. Such situation led to the purchase of high-performance desktops with CPU servers that had bigger memory and direct attached storage. The first 2 generations had a data-oriented stack as a design point. Unlike its predecessors, the 3rd generation is moving towards a network-oriented stack. The first important technology shifts began to emerge during of major vendors IBM and Oracle consolidation. Early BI solutions often were installed on desktops and it was difficult to deploy enterprise software products globally. Over time the Internet became the main design point. In consequence, web-based architecture was developed, and it offered easy installation process and faster deployment options.

  1. Data about data

Realizing that analytics is an enterprise-wide function and not limited to desktop, vendors strived to develop well-managed and secure products seeing the enterprise involvement. Products were built around a metadata layer. A metadata repository stores and manages metadata.

Metadata types:

  1. Storytelling with data

Earlier BI solutions made use tools focusing on reports and dashboards. However, architecture evolvement promoted the functional development of BI solutions. It will not be difficult for a qualified specialist to make evident insights looking at a specific data set. But it’s impossible to say the same about all business participants. Information only in the form of graphs or tables is not always fully understandable for users. For comprehensive understanding of the data meaning, solutions that allow to use the storytelling technique were developed.

GoUp Chat