Organizations today are accumulating data more than ever. Traditional data management approaches, such as centralized data warehouses and siloed data marts, are struggling to keep pace with the ever-increasing volume, velocity, and variety of information. The complexity of modern data environments is outpacing the capabilities of these legacy systems and demands a more agile and distributed solution.

The modern data-driven approach comes with a host of benefits. A few major ones include better insights, more informed decision-making, and less reliance on guesswork. However, some undesirable scenarios can occur in the process of generating, accumulating, and analyzing data. One such scenario involves organizational data scattered across multiple storage locations. In such instances, each department’s data often ends up siloed and largely unusable by other teams.

With organizations prioritizing data-driven decision-making, the amount of collected and stored data is reaching historic highs. Meanwhile, organizations are democratizing access across all functions to convert this data into actionable insights. Since more users will work with sensitive data, ensuring secure access is more important than ever. Organizations must regulate and maintain the relationship between their data assets and users. Why?

Process orchestration, also called business process orchestration, is an approach to manage and organize multiple automated tasks or workflows within a business process, like ETL process orchestration. It involves coordinating data extraction, transformation, and loading tasks across various systems to create a unified data source.

Data modernization transforms an organization’s data into more usable and accessible formats, making it usable by modern applications and systems, such as cloud-native applications, IoT devices, and mobile applications. Data modernization also includes extracting, cleaning, and migrating the data into advanced platforms.

Do you know proactive fraud detection and prevention could save organizations up to a staggering $5.9 billion annually? However, gathering relevant data for this purpose is no easy task. Financial data integration plays a crucial role in the fight against fraud, enabling organizations to merge data from various sources and formats into a unified, consistent view. However, gathering relevant data for this purpose is no easy task.

Business analytics is analyzing data to find insights that inform business decisions. Fundamentally, it involves applying data analytics tools and techniques to a business setting to simplify decision-making and improve business outcomes. Often shortened to BA, business analytics includes: With the right tools and techniques, enterprises can turn raw data into actionable insights, driving strategic decision-making and sustainable growth.

The Health Insurance Portability and Accountability Act (HIPAA), established in 1996, keeps individual health information private. It introduced HIPAA EDI (Electronic Data Interchange) Standards to secure electronic health data sharing among healthcare providers, insurers, and related entities. Healthcare EDI sets rules for how data should be formatted when electronically exchanged to ensure secure and efficient communication and reduce manual tasks.

Legacy systems have been important in the growth and success of several organizations. However, as these systems and applications age, they slow down and become increasingly costly to operate and manage. As per the U.S. Government Accountability Office, operating and maintaining legacy systems consumes over 80% of IT expenses. Organizations must scale and update these systems to accommodate their evolving business needs. This is where legacy application modernization can help.