In the Loop: Democratizing Data for a Data-First Enterprise

Elevating enterprise intelligence has emerged as a top priority for driving superior operational, tactical, and strategic decisions. The best way to achieve this is to embrace digital-first approaches, invest in technology, and foster a data-driven culture that puts intelligence at the heart of decision-making. However, a cloud-based data engineering platform can empower business decision-makers by democratizing data access and enabling them to leverage valuable data for informed decision-making. This approach ensures everyone has the tools and insights needed to contribute to superior business results.

Today, collecting data from customers alone doesn’t cut it. As data sources multiply, the ability to quickly and comprehensively make the most of them to drive decisions is critical.

Generating these insights has been the exclusive domain of data experts, data scientists, and analysts. However, the importance of data democratization and empowering business decision-makers with access to valuable data is becoming apparent. Organizations that enable broader data literacy and utilization drive superior business results.

In addition, with the world having transitioned from a competitive mindset to one where collaboration reigns supreme, data democratization is the linchpin that holds it all together to deliver actionable insights with real-time data processing. Collaboration amongst various personas of data consumption is much needed across any organization.

To thrive in this data-centric environment, companies must foster an inclusive culture where individuals from diverse roles, such as marketing, finance, sales, and operations, can leverage data effectively.

In fact, many organizations recognize this potential—81% are actively pursuing data democratization as a key initiative to enhance their data-driven capabilities (source: Data Democratization Report). Data democratization is an effective way to build greater data intelligence across the organization. Research shows that organizations with higher data intelligence improve financial results by 40%.They also reported a 20% higher operational improvement.

By decentralizing data, organizations not only enable informed decisions across levels but also fuel the transformation towards a more data-minded future. This also creates an environment where the decision-making process evolves to be more reliable, responsive, and agile.

It also allows organizations to:

• Identify critical business data to manage business and regulatory requirements
• Streamline decision-making as the volume of data grows
• Free up data teams for more advanced, value-driven data work rather than having to answer tickets in the queue
• Turn data into a true competitive advantage for the entire organization

Data democratization also removes the responsibility of data exploration and analysis from analysts alone and shifts it to a broader audience. This allows the analyst to focus on more complex analyses and predictive modeling to curate insights that fuel innovation.

How Data Management Supports Data Democratization

Data democratization needs organizations to look at their data management practices and calibrate them to manage diverse, distributed, and dynamic data. Even the best analytics tools fall short in the absence of the right data management practices. This is especially true for heavily regulated industries such as the BFSI sector, healthcare, etc.

In the BFSI sector, for example, data is generated from multiple sources, like payments, purchases, deposits, claims, mortgage applications, etc. For effective decisions, this data must be available in the right format, at the right time, with the right piece of information that the business user can use to make decisions, ensure compliance, fuel innovation, or meet other important business needs.

• Elevate their existing data infrastructure and ensure that it ingests the data (structured and unstructured, historical and real-time data) correctly
• Ensure it is staged appropriately, transformed, and then stored safely
• Deliver robust analytics and insights

Additionally, big data engineering solutions can be valuable for organizations with complex data management needs particularly those dealing with massive datasets, diverse data sources, or real-time data processing requirements.These solutions offer specialized tools and expertise to ensure efficient data ingestion, transformation, storage, and analysis, ultimately enabling seamless data democratization and unlocking valuable insights that drive better decision-making.

Deliver robust analytics and insights

Robust end-to-end data management capabilities connect the right data points across technologies and processes and manage the data flow across the enterprise, bringing true data democratization a step closer. Data pipeline development services can play a key role in establishing these efficient and reliable data flows, empowering individuals across the organization to readily access, analyze, and utilize data for informed decision-making, regardless of their technical expertise.

Priority List of Focus Areas for Data Democratizing

End-to-end data management ensures that data visibility and quality are not compromised when data moves across the different stages. The data should also be able to deliver actionable insights to users in near real-time. irrespective of any pipeline modifications, changes in ingestion, incorporation of new data feeds, change management to integrate analytics reports and metrics, etc. Some of the key areas of attention when democratizing data are:

• Ensuring that structured and unstructured data, which may include on-premise historical databases, APIs, streaming data from IoT devices, SaaS apps, media, and enterprise systems, are extracted and integrated from multiple internal systems of record as well as external sources. This is essential for accurate mapping of workflows.
• Creating a robust Unified Data Ingestion Framework to help move data from relational and unstructured data sources to big data platforms like Hadoop and NoSQL. The ingestion framework must provide a proven and established pathway to optimize data migration, storage, structure, security, and performance analytics for both on-premise databases and cloud data stores.
• Employing advanced expertise with staging methods and tools to transform the data from data lakes by removing duplicates and data silos and securing and aggregating data in the staging phase.
• Building appropriate staging zones to stage data from both on-premise and on-cloud systems with appropriate tools and accelerators to improve the efficiency of the ETL workflows.
• Developing accurate data warehousing capacities for robust analysis and reporting. Integrating databases into data warehouses has become essential to driving elevated and actionable insights and reducing data processing times. Migrating data pipelines from an existing or traditional warehouse to a big data warehouse also becomes an important consideration. This is especially important for industries like banking and finance since they deal with heavy operational data frequently.
• Contextualizing organization-wide data across key business systems, devices, people, and processes with customized, operation-specific data visualization to deliver data insights using intuitive dashboards and attractive, customizable graphs and charts.

Summing Up

Data democratization removes the barriers that impede organizational capabilities to use data assets to the fullest. It is a game changer that ensures no gatekeepers create a bottleneck at the data gateways. It ensures that anybody can use data at any time to make decisions without any barriers to access or understanding. For instance, Airbnb’s home-grown self-service data discovery platform, Dataportal, lets employees perform unified searches and explore content and data from across the organization.

The right solutions that drive data insights at every stage of the data pipeline, from source to implementation and beyond, ensure that the data is synergistic with the organizational goals. The data then helps increase profit margins and discover new sources of innovation and growth.

Connect with us to get the ball rolling to become a data-driven business with an effective and smart data democratization strategy.