#BI

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.

5 key BI tool features for successful integration

It’s difficult to imagine decision-making process without data. Current business uses BI tools that can change «rules of play». The main tools’ benefit, besides data analysis, is the ability to make in-depth insights and organize effectively specialists’ work to optimize business activities.

BI tools are designed to help organizations in decisional process. Every tool has its own unique traits and abilities. But there are some factors that promote a successful integration with the company.

  1. Data storage

Regardless of the fact that many companies already have cloud or local data warehouse at the time of BI tool implementation, the presence of a dedicated cloud solution not to come amiss. Such option can massively simplify an integration process for a company that works with limited data warehouse.

Tableau – this platform offers the most limited data storage solution that can be deployed only from Salesforce cloud solution;

Power BI – data storage can be deployed from local servers and using Azure Microsoft cloud solution;

Qlik Sense – this platform allows to deploy data storage from private, public cloud, local servers or three variants combination. The benefit is cloud independence that allows to use different cloud solution.

  1. Embedded analytics

BI tools are often integrated in mature companies with developed and optimized workflows. An ability to implement analytical mechanisms into business applications and systems promotes workflow issues minimization.

Tableau – dashboards can be embedded throughout the workflow, but other metrics and individual values are not available for embedding;

Power BI – almost every qualification user has a possibility to embed different objects. But this tool doesn’t prioritize API, so users can have difficulties with setting up;

Qlik Sense – this tool allows to embed metrics, individual values, numbers, entire and partial dashboards within edge devices, portals and workflows. Another Qlik Sense benefit is API prioritizing that provides free start.

  1. Use cases

Users need to have a possibility to use BI tool on any application or process for any goals and in any context (research, visualization, report generation and other necessary tasks).

Tableau – this tool covers several use cases that are related to visualization;

Power BI – this tool provides more comprehensive offer using Microsoft products;

Qlik Sense – one interface for all use cases allows users to familiarize themselves quickly. Also, it helps to maintain efficiency throughout the workflow.

  1. Data accessibility

Data access doesn’t have to be limited to just a few users. However, the opposite situation when many people can correct the content without proper verification is also unacceptable.

Tableau – a workbook is created by user on his hard drive and after sent to a single server IT double check;

Power BI – authors have self-service access, other users can also explore the content but with limited interactivity. The completed content is sent to a central server for validation and after it is available for circulation;

Qlik Sense – this tool provides end-users with more options. Authors, end-users and other participants between them work on the same server. This enables IT department to validate content of its own and manage content without the intermediate steps.

  1. Work mechanism

BI tools provide deep analysis and understanding with the help of powerful data analysis software. The main goal is to provide the most effective solution that will drive business growth.

Tableau – it works on SQL database using query-based approach;

Power BI – it also works on SQL database and provides solutions from query-based searches;

Qlik Sense – an associative approach is one of the tool’s benefits. Explored data sets are broader, users can identify connections and patterns that can be missed in a typical data engine.

Using BI tools in business activities particularly Qlik Sense, companies get big possibilities for business improvement. They can identify connections and patterns, assess risks and define new development options.

10 up to date BI terms

Man of today is an active user of advanced technologies. Every day each of us deals with different technologies that lighten and improve the life: internet, smartphones, messengers, cloud data warehouse, online banking etc. Business also doesn’t stand apart and implements different technologies to optimize its operative activity. It’s difficult to imagine that all these technologies can get along without analytics. In spite of its not always proper and effective usage, the practice necessity is out of questions and doubts. Data is a valuable company resource that deserves attention and analytics the relevance of which continues to grow. Let’s consider 10 key words of business intelligence 2021.

  1. Embedded Analytics – analytical content integration into business process applications. With the help of this decision there appears possibility to get all necessary information. In addition, users work efficiency and ability to solve complex business tasks improves.
  2. Cognitive computing – this is the trend of the last few years, without doubt. Every day «tons» of data are generated, and work with it is overwhelming for human brains. The main ability of this technology is to process a huge amount of structured and unstructured data and transform it into valuable information.
  3. Data accuracy – effective business decisions can be made using accurate data. This is the first and the main rule of the valid business analytics. Understanding it company management begins to focus more on an organization of the effective data management process. For example, COVID-19 situation has shocked the whole world and affirmed the importance of accurate data ownership. All people wanted to know the truth concerning number of infected, vaccinated, mortality etc.
  4. Decision intelligence – new and important discipline of artificial intelligence age that is oriented to transform information into the best practical solution. This discipline is a complex of data science, social sciences, decision science and management science. Using decision intelligence organizations can improve their operative activity, literacy, project management effectiveness, strategy management and decision-making procedure.
  5. Predictive analytics – is indispensable business tool. Advanced analytics technologies give an ability to forecast event and decisions results that help to prevent risks or mitigate effects. This tool promote business to reach new level.
  6. X-Analytics – not always data analytics relates to numbers. Analyzed business data can be in different types: text, video, audio etc. To gain competitive advantage it is necessary to analyze such data too. X-Analytics sense is to make different type analytics of structured and unstructured data (video analytics, text analytics, audio analytics etc.).
  7. Mobile Analytics – the growth of mobiles usage has instigated appearing of mobile analytics necessity. Mobile decisions implementation and usage in business give many benefits specifically data access in any time and in any location. Also, mobile analytics allows companies to get access to data in real-time mood in any place.
  8. Augmented data management – the task №1 is to provide data security and quality for real-time analytics. But it is quite difficult to make. In this case augmented data management helps to realize it. Gartner’s and Deloitte’s reports affirm this trend and accent benefits that could be achieved by artificial intelligence and data management combining.
  9. Prescriptive analytics – users’ prescribing all possible actions that they have to perform. The main task is to help specialists to choose the correct predictive model for the best decision achievement.
  10. Collaborative BI – is the combination of social media and other advanced technologies with online business analytics. It serves as a powerful tool for business to make rapid and effective decisions.

Focus on human resources determines business success

Many business leaders agree that data is their valuable intellectual property. Meanwhile a considerable part of them either don’t have an exhaustive understanding of its value or don’t know how to arrange data governance correctly. Chaotic investments in advanced technologies implantation don’t solve a problem and sometimes it aggravates the situation.

Don’t forget that data governance is a process but not a software tool. The stuff plays the key role in any processes and specifically in data governance. According to «Big Data and AI executive survey» report 93% of respondents considered people as the biggest obstacle to data governance; 40,3% of respondents cited a lack of organizational alignment as their main problem; 24% of respondents identified cultural resistance as a leading factor in failing to adopt data governance.

Many companies still view data as a byproduct of business processes and they lose possible benefits because of proper analytic resources lack inside company. Only a few organizations use data to diversify business models for effectiveness improvement and new solutions generating. That’s why company management should pay more attention to human resource, education and cultural and behavioral changes.

Why does a human factor have a strong impact on data governance?

This situation is due to the human nature of resistance to any changes. According to business coach Tony Robbins assertion 92% of the 17 million people who try to quit smoking fail; 95% of people who lose weight can’t keep longterm result. Only 10% of people have exact goals and 70% of them can achieve their goals. Furthermore, there are 2 motivating forces for human: to avoid pain and to get pleasure. And the process of learned behavior changing is not always about it.

What solution can be good?

Data governance implementation has to be planned properly and DataLabs team can help to solve this task. Also, it needs to run parallel with the implementation of corporate changing system. System includes common vision for change, strong leadership to communicate this vision, educational strategy for employees and other stakeholders, «plan B» in case of unexpected circumstances and rewards.

Human resistance problems are solved individually in each case. But the important management task is to arrange a favorable environment for employees specifically:

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