The big data explosion has given rise to data-driven decision making. And while traditional relational databases continue to perform well at processing large volumes of structured data for business insights, the deluge of raw unstructured data pouring in from multiple sources calls for a more powerful solution---which is where the Hadoop big data analytics platform comes in.
Through the use of Hadoop in conjunction with other business intelligence tools, organizations can capture, store and analyze massive volumes of valuable unstructured data to unlock the unique and actionable insights that lead to better decisions and competitive advantage.
What follows is a look at the rich and unique insights that Hadoop brings to business intelligence.
Data-driven decision-making requires the collection, integration and analysis of massive amounts of data from both external and internal sources. Of that data, only 20 percent is structured and readily analyzable. The remaining 80 percent is unstructured or “messy” and cannot be analyzed by traditional relational databases. As a result, companies have been making critical decisions based on insights gleaned from only 20 percent of the available data.
In contrast, BI on Hadoop allows organizations to collect, store and analyze all data, both structured and unstructured. This means that companies can leverage all available data to discover previously hidden relationships, trends and patterns and gain deeper insights that drive better decisions.
The social media explosion alone has resulted in massive volumes of unstructured sentiment data that is loaded with insights about customer likes, dislikes, attitudes and behaviors. Hadoop allows organizations to drill down into sentiment data and extract deeper customer insights to inform new and better products and services and enhance the customer experience.
In order to query large volumes of raw unstructured data, traditional relational databases must first put the data into a traditional form. This requires the data to be moved and copied multiple times, resulting in data that is fragmented instead of being consolidated. As a result, each department within an organization ends up with its own vertical data stack, and its own data reality, which calls the integrity of the data---and the accuracy of the insights that may be derived from it---into question.
The Hadoop analytics platform is purposely built to accommodate both the scale and variety of big data. Unlike traditional solutions, Hadoop eliminates the need to move and copy data. Instead, Hadoop consolidates all the data into a data lake, a single source of reality where data is queried in place, in its original raw and unstructured form. By preserving the integrity of the natural data, Hadoop helps to ensure that the insights derived during analysis are more accurate and trustworthy.
In today’s competitive business arena those organizations that can gain insights sooner than later and act on them quickly have a distinct advantage. Unlike traditional databases, which can take days or weeks to perform tasks, Hadoop can perform mission critical tasks in just minutes or hours. However, true competitive advantage lies in the ability to analyze data interactively in real-time, as it streams into the system, and Hadoop can handle that too. Real-time data analysis means faster time to insight, and faster time to insight gives key decision-makers the speed and flexibility they need to take quick and strategic action.
A big disadvantage of the traditional data warehouse is that valuable business information that could yield powerful insights often lies trapped in vertical data stacks and can’t be shared between departments. Complex technical barriers that business users can’t break through without advanced degrees in data science further obscure data insights.
Hadoop, on the other hand, allows business users to interact with data in a business way, by getting all of the technical stuff out of their way. After all, business users want to consume data in its natural form, and in a way that makes the most sense to them. Hadoop’s single semantic layer enables business users to leverage other powerful BI tools such as Excel, Tableau, and Qlik, to gain intuitive insights from complex and chaotic data.
The era of data-driven decisions has arrived. As big data gets bigger and more complex, organizations looking to gain competitive advantage will come to rely less on traditional approaches and more on the unique and actionable insights that the Hadoop analytics platform brings to business intelligence.