Leveraging Enterprise Analytics to Harness the Power of Big Data

We rely heavily on data, and today’s organizations deal with large volumes of it from various sources.

In recent years, data—and data usage—has grown at an unprecedented rate. It was estimated that in 2023, we created, captured, and consumed a total of 120 zettabytes of data, with the average person producing 102 MB every minute. By 2025, the amount of data we create and consume is projected to grow to over 180 zettabytes.

How can modern organizations harness the power of big data to drive sustainable growth? Sifting through even a small fraction of that data to find how much of it is useful is a challenge, and extracting value from it even more so.

Enterprise analytics empowers organizations, allowing them to effectively use data to identify patterns, make informed business decisions, implement actionable change, and maintain a strategic advantage. It is the process of collecting, organizing, and analyzing big data, and transforming it into practical insights.

For example, you can use enterprise data analytics to understand trends like declining sales in certain regions. Once you’ve identified the root cause, such as poor customer experience or ineffective marketing strategies, you can roll out corrective measures.

In this article, we’ll discuss what enterprise analytics is, its role within an organization, and key enterprise data analytics strategies you can use to drive organizational growth.

The Role of Enterprise Data Analytics in Modern Business

Data-driven organizations are more likely to succeed and get better results. In a study by the Harvard Business Review, organizations using a data-driven approach were in a much better position to thrive in the face of a crisis. They’re also more profitable.

Enterprise data analytics drives business transformation and growth. Large businesses across industries like consumer packaged goods, manufacturing, and retail are using enterprise analytics to analyze large datasets from various sources, track performance metrics, and examine marketing data.

For example, in the retail industry, businesses can use enterprise analytics to analyze consumer behavior. Using these insights, they can enhance and personalize their marketing campaigns.

Let’s say you’re a company that specializes in cross-platform app development. You’ve built a new mobile app and now you want to gain insights like how people are interacting with your app or if you’re hitting your targets. Mobile app data analytics gives you actionable insights you can use to improve your app, keep track of your KPIs, and modify strategy and tactics to fuel progress.

Meanwhile, in the SaaS industry, data analytics plays a key role in product development. SaaS data analytics helps companies identify the most popular features, understand how users interact with their applications, and analyze user behavior and preferences. Using enterprise analytics to address these issues enables companies to enhance user satisfaction, which can lead to better engagement and retention.

Enhance Customer Experiences

You may think you know what your customers want but customer data—including their feedback and behavior—shows you the actual truth. Enterprise analytics lets you segment your customers based on factors like their demographics. This paints a clearer picture of your target audience, their pain points, wants, and needs. You can then use these insights to tailor your customer interactions, campaigns, or messaging, which can help boost customer satisfaction and loyalty.

Unlock New Opportunities for Growth

Data drives growth and success. For instance, using historical data to forecast future trends and analyzing customer segments to uncover behavioral patterns can help businesses identify new growth prospects and maintain their competitive advantage.

Improve Operational Efficiency

Enterprise analytics lets you identify bottlenecks, inefficiencies, and areas for improvement in your business processes or operations. You can then take measures to streamline these aspects, optimize resource allocation, reduce waste, and save on costs.

Better Risk Management

Planning to expand your operations comes with a certain level of risk, and being able to anticipate and mitigate such risks can help you achieve sustainable growth. By analyzing relevant data, you can better foresee issues, identify the best strategies to manage these risks, and make data-driven decisions.

Foster a Culture of Innovation

Knowing how to use and respond to data insights helps organizations quickly pivot their strategy to meet evolving customer and market demands. Enterprise data analytics makes use of technology, but it can only do so much. For it to be effective and give you lasting business outcomes, you need to build the right culture within your organization. Cultivating a culture of innovation—one that encourages rapid experimentation—can help organizations progress faster, achieve better outcomes, become more agile, and stay ahead of the curve.

Key Strategies for Implementing Enterprise Analytics

Insights-driven organizations have a strategic advantage over their less insights-driven counterparts. A 2023 research by Forrester found that organizations possessing higher levels of maturity, in the context of their being insights-driven, are more likely to achieve substantial benefits when it comes to their results.

According to the study, an advanced insights-driven business is 2.8 times more likely to achieve double-digit year-over-year growth. It’s also 1.5 times more proficient at mitigating compliance risks compared to beginner firms or less insights-driven ones.

Effective enterprise data analysis requires a comprehensive data strategy that covers components like data acquisition and data visualization. For instance, when acquiring data, your data strategy can help you find relevant sources based on factors like your business needs or objectives. During the data visualization and communication stage, for example, a clear strategy provides you with standards on how to best present data to ensure that it will be easily understood by your target audience.

Having a comprehensive and long-term plan gives your organization a clear roadmap for the effective implementation of your enterprise analytics initiatives. When developing a tailor-made enterprise analytics strategy, keep these points in mind:

• Have clear and well-defined goals and objectives. What outcomes do you want to achieve through enterprise data analysis? Without goals and objectives, you run the risk of running unfocused and disconnected analyses, which make it difficult to effectively measure the impact of your enterprise analytics initiatives.
• It should align with your business needs and must be scalable to accommodate evolving requirements.
• You must be able to consistently implement your strategy within the entire organization.
• Use the best reporting and visualization tools to create well-designed visualizations. The right tools can help you effectively turn complex data into easy-to-understand graphics that you can share with your audience or within the organization.

With that in mind, here are three key strategies for implementing enterprise data analytics to drive organizational growth.

Build a Strong and Scalable Data Infrastructure

Having a well-defined and scalable data infrastructure can help improve your data quality and consistency. It can streamline your business processes, which then helps optimize your costs. It facilitates enhanced collaboration while allowing you to become more agile and capable of adapting your strategies according to evolving data needs.

Before building your data infrastructure, plan for data security. What security measures will you be implementing to maintain data integrity and prevent unauthorized access? Will you be able to incorporate real-time analytics?

Once you’ve laid the foundations for your scalable data pipeline, keep the following points in mind:

• Identify your data needs, how the data will be used, and who will be using it.
• Pick a suitable database. If you want a structured format, you can opt for relational databases. If you require more flexibility, consider NoSQL databases. If you want a hybrid database, it’s worth looking into NewSQL databases.
• Future-proof your data infrastructure by integrating emerging technologies and platforms like cloud-based data platforms, AI, and ML into your data infrastructure.

Foster a Data-Driven Culture

Around 81% of leaders have an enterprise strategy for creating a data-driven culture. Developing a data-driven culture within your organization is necessary if you want your company to stand out, stay relevant, and maintain your competitive advantage.

According to a DataCamp report, 42% of leaders say that data-driven decision-making is a very important skill to have on their teams. This is followed by 34% of leaders who consider data visualization interpretation skills to be very important and 38% who see data analysis and manipulation as critical skills. By “data-driven culture,” we mean relying on fact-based statistical information to make informed decisions instead of going with your gut or intuition. To build a thriving data-driven culture in the workplace, you must:

• Make data accessible to authorized and relevant parties, while ensuring that you have safeguards in place for privacy and security.
• Have data trust, which means you’re confident in the quality and integrity of your organization’s data.
• Have leadership buy-in. Your leaders must be data advocates themselves. They should ideally be good role models for your organization in the context of how to utilize data effectively, promote data literacy, and champion data-driven decision-making.
• Train your staff and get them involved. You can organize trainings or workshops to update their skills and help them understand the role and importance of data within your organization.

Shifting to a data-driven culture unlocks several benefits, such as:

• Improved decision-making capabilities
• Enhanced productivity and efficiency
• Better transparency and employee engagement

More than building a data-driven culture, you must be capable of maintaining it to ensure sustained organizational growth. You can do this by monitoring your initiative’s progress, recognizing and rewarding employees who are proactively practicing data-driven decision-making, and encouraging innovation.

Ensure Data Quality and Proper Governance

Establish checks to ensure the quality, accuracy, and integrity of your data. Create data validation rules to check for discrepancies or anomalies in your data. Regular data cleaning also helps spot errors or duplicates.

Meanwhile, proper data governance ensures that your data is usable, secure, and available. It helps your organization get quicker access to useful data, which allows you to make better business decisions. It also improves regulatory compliance, and risk mitigation, and helps assure customers and other stakeholders that their data is protected.

Similar to the checks you must perform to ensure data quality, data governance entails creating internal standards or policies concerning how data is collected, stored, utilized, and disposed of. It involves several components including data cataloging, data quality, and data classification.

A good data governance initiative can entail storing your data in a data lake with unified data access controls. It also involves several stakeholders, including a Chief Data Officer, the data owners and stewards, and a governance committee that’s responsible for creating data governance-related policies.

Storing all your data in a data lakehouse, for example, gives you better end-to-end visibility while making it easily discoverable to authorized users.

Potential Challenges in Implementing Enterprise Data Analytics

While data is a key growth driver, many organizations still grapple with how to properly harness and utilize it. Enterprise data analytics makes data make sense. However, the process of developing and implementing a data analytics strategy comes with several challenges.

Data Quality

Is your data accurate and reliable? Working with inaccurate, incomplete, inconsistent, duplicate, and even non-standardized data can lead to erroneous insights, which can affect your decision-making. To ensure you’re using high-quality data, implement measures such as data validation and governance.

Data Privacy and Security

Organizations will need to reassess their data privacy and security protocols. Are you regulating access to critical operational systems? What security measures, such as access controls and secure data storage, are you implementing? You may want to consider setting up a data classification system that covers aspects like what kinds of data you collect, how they’re categorized, and who has access to which kinds of data.

Additional considerations worth looking into include:

• Whether or not your data analytics system is compliant with data privacy regulations when it comes to processes like data collection and distribution
• The scope of your existing compliance framework, and if it needs to be updated
• Proper training for employees when it comes to data handling and access controls

Data Silos

Large companies, especially those that have several departments and practice software development outsourcing, often deal with fragmented data, which is difficult to consolidate and analyze. Furthermore, when data is stored in isolated silos, it prevents effective collaboration and can give you fragmented insights.

Granting data access to your entire organization is one way to break down data siloes. However, when democratizing data, you must have measures in place, such as a centralized repository, to safeguard it against unauthorized access. Implementing clear data governance policies also helps ensure that your data remains consistent and secure.

Talent and Skills Gap

Organizations, regardless of their size, may find it difficult to effectively utilize large volumes of data because of skill shortages and knowledge gaps when it comes to data analytics solutions. To overcome this challenge, you can:

Train and upskill employees to help them acquire enterprise data analysis skills. Provide them with resources like paid training programs or online courses.

Utilize advanced analytics tools to help streamline your workflow and cover tasks like data preparation and cleaning.

Create a data literacy program for your employees. According to a 2024 Gartner CDAO Survey, poor data literacy is one of the top 5 challenges preventing data and analytics success. Not only does having a comprehensive data literacy initiative help create a data-driven culture, but it also empowers your employees by helping them understand and use data more effectively.

Managing Resistance to Change

When you introduce something new that can potentially change how your organization operates, you’re likely to encounter some backlash or resistance. Peers and even leaders may feel challenged by this shift, as it will require them to adapt to an entirely new system.

To prepare your organization for enterprise analytics, you must roll out a comprehensive organizational change management plan. This entails understanding your teams’ data needs, collecting user feedback, and showing them how enterprise analytics can give them better insights, improve their workflows, and enhance their decision-making capabilities.

Finding the Right Platform

Finding the best enterprise analytics platform is an entirely different challenge. It should provide accurate insights, comply with industry standards, and come with robust security measures. Aside from these factors, you also need to consider its scalability, ease of use, and accessibility.

But, most importantly, you have to understand the complexities that come with using big data and why your business needs data analytics in the first place. What is your business use case for enterprise data analytics? Can a particular platform work with different data types and databases? How does it fit into your data integration and management architecture?

A reliable software development company can craft tailor-made solutions to help you transform data into strategic assets. Taazaa’s data analytics engineering services, ranging from Big Data Implementation to custom application development are designed to help you make the most out of your data. Connect with our solution consultants to discuss your business needs today.

Driving Sustainable Growth Through Enterprise Analytics

Implementing enterprise analytics requires a lot of time, effort, and resources from organizations. You’ll be required to shift how you approach all things data, from collection to distribution. You’ll also need to provide your employees with the right training and tools, promote data literacy, and get executive buy-in. You need to make sure that your data analytics initiatives align with your business goals and objectives.

While demanding, enterprise analytics is a worthwhile endeavor. When done well, you can transform your company into a data-driven organization that’s capable of harnessing and utilizing vast amounts of data and turning them into practical insights.