The concept of�Business Intelligence�evokes solutions for advanced reporting, exploitation of data marts, and sophisticated algorithms for the synthesis of large quantities of unstructured data to support management decisions.�The result is a sort of crystal ball, with a little more scientific rigor, capable of helping the company to keep the right course to achieve specific objectives.�In reality, it was born long before there were computers and�software when at the end of the nineteenth century the essential role of the collection of precise data was already understood as a prerequisite for the success of any business.

Business Intelligence was born in the late nineteenth century when the role of collecting precise data for the success of any business was already understood.�the first BI tool that every manager had to deal with was a more or less personalized Excel sheet, with the flood of information that companies, sometimes unwittingly, have available in our day, to apply good Business Intelligence practices it becomes indispensable to react promptly to sudden changes in the market.

For this reason, it is no wonder that Gartner has indicated investments in Business Intelligence as the primary objective of CIOs at least until 2022, with an estimated market for Advanced and Predictive Analytics in 2 billion dollars worldwide for 2020.

In India, the situation is well summarized by the Nextvalue research published in the Assintel 2019 report, according to which 51% of medium-large companies and 45% of small and medium-sized ones have included 2019 or 2020 projects related to Business Intelligence in the portfolio, which in both cases is the choice most often indicated among all types of investment in software and services.

The pyramid of Business Intelligence

Currently, there are solutions of all kinds for BI, in�the cloud�or on-premises, suitable for large and small organizations, but we must not confuse the concept with the Business analytics tools which, as far as the cutting edge of the procedure is concerned, is only a component of the wider design that a company should consider to enable a future-proof Business Intelligence system.

The system can be conceived as a pyramid, in which more distilled data are obtained at each level, up to the extreme synthesis: a dashboard that constitutes the real decision support.�At the base of the pyramid, there are multiple sources of information, such as files, documents, and�databases, from which often fragmented and unstructured data are extracted.�The next level takes advantage of Data Warehouses and Data Marts to achieve better organization and important skimming.�The next phase involves the application of statistical analysis techniques and OLAP (On-Line Analytical Processing) that allow you to process large quantities of information very quickly, obtaining only the significant elements.�The next step is the so-called data mining.�It is here that the most sophisticated algorithms intervene in search of what can represent an anomaly, a risk, or an important suggestion to predict the progress of the business.

This important information must then be made available to decision-makers in the most immediate and understandable way possible, making use of experts in visualization techniques and reporting. Everything must work as quickly as possible so that management can respond immediately to critical issues and opportunities.�In this process, Business Analytics is the explanatory and predictive element of data analysis, thus representing the most delicate phase of the Data mining process.

How to get valid analysis with BI

If the base of the pyramid is constituted by a large amount of data available, the quality and homogeneity of the latter become the cornerstone of the whole procedure and the real discriminant for obtaining reliable analyzes and forecasts.�If the number of information today is almost never a problem, its completeness and reliability is very often a factor of uncertainty, which no one, however rigorous, implementation of a BI system can remedy.

For each level of the pyramid, it is therefore appropriate to act on the data to solve specific problems. With the basic sources it is necessary to make the data uniform and comparable, while in the transition to the Data warehouse, it is necessary to clean the archive from inaccurate data or correct them, eliminating the empty fields.

Before entering the Data Mining phase, it is also important to eliminate the duplicates and make sure that the set of preparatory information for the analysis is complete.�The visualization and reporting phase is also not immune to the risk of errors.�In this case, the elements to be verified are the uniqueness of the indicators and the correctness of the formulas used to represent the results.

BI in the Cloud for Small Business

Given the complexity of the process and the involvement of the entire technological infrastructure of an organization, one could think of BI as suitable only for medium and large companies.

In reality, the possibility of subscribing to Cloud-based BI services in SaaS mode has opened the doors of predictive data analysis even to small businesses, without having to have a specialized staff and avoiding the complexity and costs of an on-premises solution.

From IT manager to business analyst

Gartner predicted that most of the managers and analysts in the company will have tools available to prepare and evaluate data in a completely autonomous way, without needing to be supported by the IT department.�The trend is that of decentralization of Business Intelligence towards business units, with the consequent risk of the proliferation of similar tools within the same organization, each with only partial access to data and without centralized control.

This, in addition to the apparent ease of use of the new tools, is also due to the actual difficulties of corporate IT in meeting the growing needs for speed and flexibility in reporting.�Furthermore, it is not certain that those with IT skills also have the business vision necessary to design and make analytics efficient.

This scenario paves the way for the emergence of new professional figures, with a view to retraining IT workers, who would straddle the two worlds becoming fundamental resources for the harmonious development of Business Intelligence in the company.

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Business Intelligence (BI) plays a crucial role in helping organizations forge ahead of their competition and become future-ready in the face of disruptive technologies.

Characteristics of Business Intelligence (BI)

1. Predictive Analytics and Scenario Planning Business intelligence offer advanced predictive analytics capabilities that enable organizations to forecast future trends, market shifts, and customer behavior patterns. By analyzing historical data and applying machine learning algorithms, Business intelligence solutions & tools can identify emerging patterns and provide insights into potential future scenarios. This foresight allows businesses to anticipate disruptions, proactively adapt their strategies, and make informed decisions to stay ahead of the competition.

2. Identification of Emerging Opportunities Disruptive technologies often create new market opportunities or disrupt existing business models. Business intelligence solutions can help organizations detect these emerging opportunities by analyzing vast amounts of data from various sources, including social media, market research, and industry reports. By uncovering hidden trends and patterns, BI empowers businesses to identify and capitalize on new revenue streams or pivot their offerings before their competitors.

3. Customer Intelligence and Personalization In the era of disruptive technologies, customer expectations are constantly evolving, and personalization is key to delivering exceptional experiences. BI tools provide businesses with in-depth customer intelligence by analyzing data from multiple touchpoints, such as online interactions, purchase histories, and feedback. This insights into customer preferences, behavior, and sentiment enable organizations to tailor their products, services, and marketing strategies to meet specific customer needs, fostering loyalty and staying ahead of the competition.

4. Operational Excellence and Agility BI solutions offer real-time visibility into operational processes, enabling businesses to identify bottlenecks, inefficiencies, and areas for optimization. By leveraging BI insights, organizations can streamline their operations, reduce costs, and improve responsiveness to market changes. This operational agility and efficiency allow businesses to adapt quickly to disruptions, outpace competitors, and remain future-ready.

5. Data-Driven Innovation Disruptive technologies often necessitate innovation to stay relevant and competitive. BI provides a data-driven foundation for innovation by enabling businesses to explore what-if scenarios, test hypotheses, and validate ideas using historical and current data. By analyzing market trends, customer feedback, and performance metrics, BI empowers organizations to develop innovative products, services, or business models that cater to evolving customer demands and market dynamics.

6. Collaborative Decision-Making BI tools facilitate collaborative decision-making by providing stakeholders with consistent, up-to-date, and visually compelling information. Interactive dashboards and self-service analytics enable cross-functional teams to access and analyze the same data, fostering alignment, transparency, and informed decision-making. This collaborative approach helps organizations respond swiftly to disruptive changes and make strategic decisions that keep them ahead of the competition. By utilizing the power of BI, businesses can gain a comprehensive understanding of their operations, customers, and market dynamics, enabling them to make data-driven decisions, anticipate disruptions, and seize emerging opportunities. BI empowers organizations to be agile, innovative, and future-ready, ultimately positioning them to forge ahead of their competition in the face of disruptive technologies.

Unlocking the Strategic Value of Business intelligence solutions in the Age of Disruptive Technologies

In the rapidly evolving digital landscape, where disruptive technologies are reshaping industries and redefining business models, the role of Business Intelligence (BI) has become increasingly pivotal. BI, with its ability to transform raw data into actionable insights, empowers organizations to navigate through the complexities of emerging technologies and stay ahead of the competition. Let?s delve deeper into the importance of BI in this era of disruption.

1. Mastering the Data Deluge Disruptive technologies such as the Internet of Things (IoT), cloud computing, and big data have led to an unprecedented surge in the volume, velocity, and variety of data generated. Traditional data management and analysis methods are often overwhelmed by this data deluge. Business intelligence solutions provide powerful tools to collect, process, and analyze these vast amounts of data from multiple sources, enabling organizations to extract valuable insights and make informed decisions. By leveraging advanced data mining techniques, Business intelligence tools can uncover hidden patterns, trends, and correlations within the data, allowing businesses to gain a deeper understanding of their operations, customer behavior, and market dynamics. This comprehensive view empowers organizations to optimize processes, identify new revenue streams, and make data-driven strategic decisions.

2. Driving Digital Transformation Digital transformation is no longer an option; it’s a necessity for businesses to remain competitive and future-proof their operations. BI plays a pivotal role in this transformation by providing a comprehensive view of an organization’s operations, customer behavior, and market trends. With BI tools, companies can identify areas for optimization, streamline processes, and uncover new revenue streams, ultimately driving their digital transformation efforts. By leveraging predictive analytics and scenario modeling capabilities, BI solutions enable organizations to anticipate market shifts, respond quickly to changing customer preferences, and proactively address potential risks or opportunities. This agility is essential in the fast-paced digital landscape, where disruptive technologies can rapidly disrupt established business models.

3. Enhancing Data-Driven Decision-Making In the era of disruptive technologies, the ability to make timely and data-driven decisions is paramount. Business intelligence solutions equip decision-makers with real-time analytics, interactive dashboards, and predictive modeling capabilities. These tools enable organizations to access and analyze data from various sources, including structured and unstructured data, enabling them to gain a comprehensive understanding of their operations and market dynamics. With BI tools, decision-makers can visualize complex data sets, identify trends and patterns, and leverage advanced analytical techniques to uncover insights that would otherwise remain hidden. This data-driven approach to decision-making empowers organizations to make informed choices, mitigate risks, and capitalize on emerging opportunities, ultimately driving business growth and profitability.

4. Fostering Innovation and Agility Disruptive technologies often disrupt established business models, requiring organizations to be agile and innovative. BI empowers companies to experiment with new ideas, test hypotheses, and rapidly iterate based on data-driven insights. By leveraging BI, businesses can identify emerging trends, uncover new market opportunities, and develop innovative products or services that cater to evolving customer demands. Furthermore, BI solutions enable organizations to monitor and analyze the performance of their innovations, allowing them to make data-driven adjustments and optimizations. This iterative approach, fueled by BI insights, fosters a culture of continuous improvement and innovation, enabling businesses to stay ahead of the curve in the face of disruptive technologies.

5. Driving Competitive Advantage In today?s hyper-competitive landscape, the ability to leverage data effectively can be the differentiating factor between success and failure. BI solutions provide organizations with a competitive edge by enabling them to gain a deeper understanding of their customers, optimize operations, and make informed strategic decisions. By harnessing the power of BI, businesses can stay ahead of the curve and outperform their rivals. BI tools empower organizations to identify market trends, customer preferences, and emerging opportunities before their competitors, allowing them to proactively adapt their strategies and capitalize on new market dynamics. Additionally, by optimizing operations and streamlining processes through BI insights, businesses can achieve greater efficiency, reduce costs, and ultimately offer better products or services to their customers.

Conclusion

As disruptive technologies continue to reshape industries, the importance of BI cannot be overstated. By embracing BI, organizations can unlock the true potential of their data, driving innovation, agility, and a sustainable competitive advantage in the ever-evolving digital landscape. BI has become an indispensable tool for businesses seeking to thrive in the face of disruption, enabling them to make informed decisions, foster innovation, and stay ahead of the competition.

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