Cross the barriers and win actionable data insights

According to NASSCOM, India has the second-largest internet user base globally; a figure we continue to see accelerate post the pandemic’s peak as consumers continue to move online and small businesses digitise. As of June 2020, India had an internet subscriber base of 749.1 million, which is expected to cross 1 billion by 2025. This has led to an increase in the amount of data generated and consumed. In 2019, Indians consumed the highest amount of data per month globally at ~12GB, which is expected to double over the next five years.

As data volume and variety increase and data sources proliferate, new opportunities will arise to deliver superior customer experiences, drive better business decisions and enable greater agility and resilience. New technologies and approaches – such as the internet of things (IoT), cloud-native development, artificial intelligence (AI), machine learning, and the modern data fabric – offer a path to this intelligent business vision.

Despite these opportunities and new approaches, businesses are struggling to manage data and generate meaningful analysis. They’re weighed down by issues such as dirty data, misaligned data collection and governance policies. These companies risk falling behind competitors, who are using data intelligence to adapt to their customers’ needs quickly and proactively. To gain actionable insights from data, one needs to address some common barriers. Let’s take a look at each of them.

Data discovery challenges

Data discovery is difficult when you have unknown data sources, poor data quality, data silos, and compliance restrictions. These issues can trace their origin to data used or generate by a specific application stored in a siloed data platform, typically found in an early 2000s web application architecture or in 1990s UNIX applications.

Additionally, incomplete views of customers and other business entities, duplicate data and a general lack of understanding around what data is available (for building new applications or updating existing ones) result in less effective services, insights, and customer experiences.

Solution: With a holistic view and understanding of your data estate, plus a modern data architecture that makes your data accessible, you can make data discovery and utilisation a more natural part of your DevOps processes and culture. DevOps drives speed and quick turnaround. And your data – if it’s known and accessible and in a useful format – can be fully incorporated into your DevOps culture, development, and deployment processes.

Excessive costs

Costs can grow out of control if your infrastructure is not structured for utility and elasticity, your talent is expensive, and you face large, ongoing investments with no guaranteed returns.

India has the second largest internet user base globally. As of June 2020, this base comprised 749.1 million people, and is expected to cross 1 billion by 2025.

Costs can also become excessive if you continue to rely on on-premises data solutions for your worst-case scenarios when you’re stuck with servicing older virtualised applications and data infrastructure, and on-premises data platforms servicing cloud-based applications may incur higher-than-needed ingress/egress fees.

Solution: By moving data platforms to the right public and private clouds in a multi cloud architecture, you get several benefits— including elasticity, self-service, optimised economics, and cloud-native services — using which you can develop modern applications and host a modern data architecture.

Complexity

Choosing the right mix of technologies, identifying architectural best practices for deployment, and integrating cloud, on-premises, and edge — these are all complex responsibilities. And they are made even more difficult if your data platform mix is not optimised.

For example, your data may have been forced into a traditional relational data management system, or worse, into unstructured files, even though that is not the optimal place for data use and analysis. This makes developing applications using this data more difficult and less effective.

IoT dramatically increases the data coming into your business. But it must be analysed and intelligently separated into data flows that support the business to the extent that your applications get the data they need and when they need it. Many organisations either do not leverage IoT or do so in a manner that overly restricts their data being used from IoT. While these approaches prevent data from flooding with reliability, security, and availability issues, they eliminate the benefits of using all of the appropriate data in the organisations’ business ecosystem.

Solution: Dealing with the explosion of data variety, velocity and volume are complex. However, by putting this data into the right data platforms and in the right clouds configured into modern data architecture, your data can be more readily used, be more cost-effective and set the foundation for modern analytics and superior business insights.

Skills gap

Most organisations do not have the necessary in-house skills to optimise their data architecture for modern AI/ML use cases and cloud-native applications. To create a modern dat fabric, you need specialised education, training, and experience, which are not organically available in typical IT teams. This skills gap results in data integration architecture that is scattered and opportunistic, which prevents applications from getting the right data at the right time and leads to less-than-optimal experiences, results, and insights.

Solution: Work with a partner whose team has the right skills, career paths, and continuous work experience, particularly the one that is always busy solving problems and building expertise across many different industries and use cases. This helps ensure that it is able to attract and retain the best data people.

Achieving actionable data insights

With modern data architecture, your data can help drive better business processes, experiences, and decisions. And with a fully integrated data environment supported by DataOps and MLOps, your business and IT teams can make intelligent business and IT decisions that will drive maximum value to your customers and have a huge impact on your business’s bottom line.

By Sandeep Bhargava, Managing Director, Asia Pacific &Japan, Rackspace Technology