In this world full of technologies, data is the most crucial thing to handle. Data-driven basically represents a strategic process of leveraging insights from data to define new business opportunities, better serve customers, expand sales, upgrade operations, and many more. It offers enterprises to use evidence-based data to produce decisions and plan carefully to pursue business objectives.

There are numerous benefits to transforming into a data-driven organization. Such organizations are the one that not only identify the importance of collecting raw data but also understands that they shouldn't make business decisions using raw data alone. Instead, they collect, analyze and derive insights from data to address business problems and drive profitability. A data-driven decision lies on empirical evidence, enabling leaders to take informed actions that finally give positive business outcomes. The opposite of a data-driven process is to make decisions based solely on speculation. For data-driven business leaders, listening to their gut may be part of their decision-making process, but they only take the action based on what the data shows. Based on the IBM report "Inside the mind of Generation D" seven out of ten respondents mentioned they are not lacking data. Instead, the key to heightening business value is how enterprises use data and sophisticated analytics.

No doubt, there are multiple benefits to transforming into a data-driven organization. Forbes studies say that these organizations experience a 27% year-over-year growth in revenue compared to 7% for other organizations, and 12% reduced operating expenses from the prior year compared to 1% for other organizations.

There are four common characteristics behind the success of every data-driven organization and they are:

Data is centralized and organized: To ensure data is fresh and relevant, data-driven organizations collect data from across the organization. They do not limit data gathering to internal sources; there are multiple external data sources that can and should be included in analytics (depending on the industry). Be aware of what data and how much you gather—information overload is an actual threat. Today, many companies are establishing data reservoirs with a combination of internal and external data. Although, it is of utmost importance that data flowing into the data reservoir is strictly controlled in order to reap the craved benefits of the investment.

Data governance policies are in place: To safeguard the quality of key master data objects like products, customers and suppliers, there should be clear data governance processes in place. According to record, master data quality falls down at a rate of 2% per month if not governed. Master data quality is the most important for high-quality analytics.

Data is accessible: In data-driven organizations, everyone is able to access some data. Almost no one has access to all of it. Data security and privacy necessity limit what data can be accessed. A guiding principle? Everyone must have access to data required to perform the job, and data should be easily accessible via different tools like smartphones, desktops, and laptops.

Analytics is integrated into tools: Analytics tools at data-driven organizations tend to be among the most innovative, with functionality to simply define analytics models. They are also immersing into existing tools, making them more comfortable to be used. Competitive advantages arise from analytics models that permits users to predict and act upon business insights and thereby optimize outcomes. At the time of analyzing data, organizations should always start with a business question.