Data-driven decision-making: Enabling Business Intelligence through automation

Today, data has become the very core of every organisation. Firms are no longer dependent on traditional approaches to make strategic or financial decisions. They rather focus on real-time insights derived from the vast amounts of data generated daily. All organisations, regardless of size or sector, have to leverage data to make educated decisions. In order to store and manage this data, organisations make use of the cloud solutions.

According to Thales’ Data Threat Report of 2022, about 60% of corporate data is stored in the cloud. The traditional infrastructure often fails to manage this scale, leading to slow decision-making and missed opportunities.

Cloud solutions, along with automation and business intelligence (BI), alleviate these challenges by providing scalable data processing and automated workflows. This further leads to a trend where organisations are progressively adopting cloud BI and automation solutions to foster innovation and efficiency.

The potential of data-driven decision making

Concurring to Salesforce’s Research, 80% of business professionals agreed to adopt data-driven decision-making, an approach of leveraging data and analytics to make strategic and operational choices. This practice includes data and insights from various sources that include market trends, financial data, as well as other relevant information. By leveraging the power of DDDM, organisations can achieve:

• Improved precision
• Enhanced operational efficiency
• Better strategic planning
• Risk mitigation
• Continuous improvement and innovation

In order to gain these benefits, organisations require tools that can manage large datasets, provide real-time insights, and seamlessly integrate them into their processes. Cloud computing, business intelligence (BI) and automation provide an excellent platform for this shift.

The growing significance of cloud BI

With organisations increasingly relying on analytics tools like business intelligence (BI) solutions in order to make data-driven decisions and improve operational efficiency, the importance of cloud BI has eventually increased.

Cloud BI merges robust data integration and business analytics along with the accessibility and flexibility of cloud technology, assisting businesses in assessing insights from anywhere. It has altered the conventional approaches companies use to interact with their data, making them more agile in responding to market changes.

The modern BI systems intend to solve two major challenges: reliance on IT and manual analysis. In order to overcome both issues, data analysts construct their models using systems that generate databases automatically. On the other hand, the second issue is handled with a new set of auto BI tools.

These solutions provide insights automatically, reducing the need for manual data analysis. Following this, MarketsAndMarkets, in its report, has projected that the global cloud analytics market will grow at a CAGR of 27.1%, reaching 118.5 billion by 2029. 

However, the process of data analytics is constrained to providing an overview of historical data or identifying the current scenario and does not generate forecasts of future possibilities on its own. It indicates that data analytics cannot be guaranteed solely with business intelligence. This is where BI automation comes in, saving data analysts' efforts and time spent investigating and integrating data.

Role of automation in unlocking BI's maximum potential

The integration of automation in cloud BI solutions helps organisations achieve maximum efficiency and make effective data-driven decisions. Automation assists businesses to uncover the maximum potential of BI in the following ways:

Acquiring Insights

BI automation decreases the human efforts required to obtain relevant business information. It uses artificial intelligence (AI) to automate reasoning and acquire insights. AI works as a continual closed-loop process in which data patterns are identified, analysed and transformed into automated actions. This also helps organisations explore beyond standard searches and recognise unanticipated alterations. Furthermore, BI automation helps businesses prioritise tasks and make more informed decisions.

Improving Data Quality

One of the most important data phases in BI is data processing, which is performed systematically and produces superior outcomes. Despite experts using their best learning algorithms, they will still perform badly if the data is not prepared. This, in turn, necessitates the integration of automation technologies that can help businesses solve the challenge of data pre-processing.

The automation is carried out through meta-learning, influencing the transformation of datasets and the final output. This further relieves data professionals from time-consuming, repeated manual chores such as finding and removing duplicates, missing information and errors.

Consequently, the successful integration of business intelligence and automation has led to the growth of the cloud industry worldwide. As per Fortune Business Insights, the global cloud computing market is anticipated to reach $2,291.59 billion by 2032.

Wrapping up

In recent times, data-driven decision-making has become imperative for every organisation, with data being its driving force. By leveraging the power of the cloud and BI automation tools, organisations can transform raw data into actionable insights, fuelling innovation and operational efficiency. As data continues to grow both in terms of volume and complexity, the significance of these technologies for organisations to remain competent cannot be overlooked. 

(Jyoti Singh is the Co-Founder at Plus91Labs.)