Data is the new oil. The world is going digital fast, and the data race has begun. With the digital transformation of businesses accelerating, organisations are increasing their investments in AI and Big Data technologies to gain a competitive edge.
Some believe that by 2023, 90% of all network traffic will be driven by artificial intelligence as systems continue to learn at a rapid pace. What does this mean for businesses? It’s time to start being data-driven from now on!
Data-Driven Companies
Digital transformation has redefined the role of businesses. They are more data-driven and technology-enabled companies, with their performance measured in real-time and their strategy aligning with their KPIs. The prevailing business environment is fast-paced and dynamic, with technological changes accelerating at a lightning speed. Businesses need to remain agile, innovative and collaborative to stay ahead of the curve.
It is not just about adopting digital technologies but leveraging data to drive business outcomes. Data is the fuel that drives artificial intelligence, machine learning and predictive analytics.
Here are six ways businesses can be data-driven in 2023:
Always be on the lookout for data sources
The first step towards data-driven business is to look for data sources. Enterprises need to go beyond their core business and look for data sources from the broader ecosystem. This is achieved by partnering with startups, data service providers, universities, and government organizations that are focused on data-driven initiatives.
Data partnerships will strengthen your data set and support your ability to quickly pilot and test new solutions. Already having a large data set will allow businesses to build services that can be applied across industries.
Leverage AI and ML to make sense of the data
Once you have a good data set, you need to make sense of it. This is where AI and ML come into play. AI can be applied to every stage of the data pipeline.
AI can assist in data sourcing, preparation, training, and model deployment. AI can help make sense of the data at each stage of the data pipeline by detecting patterns and anomalies, automating repetitive tasks, and providing insights that can drive business outcomes.
Build a data-driven culture
A data-driven culture is essential for businesses to thrive in a data-driven world. This can be achieved by creating the right environment that fosters innovation and creativity. Create a culture where data is celebrated, debated, and democratized.
Leaders should be open to receiving numbers that challenge their assumptions. Data governance and transparency are must-haves for every organization. The data-driven culture will help businesses in leveraging the full potential of data. It will also help businesses in mitigating risks associated with data.
Establish real-time analytics capabilities
Real-time analytics is the need of the hour for businesses to be data-driven. Enterprises are empowered with the ability to generate insights in real-time.
Decision-making can be made on the go, based on the latest data and insights. Data integration and governance challenges can be overcome with the help of technologies like Apache Kafka, Apache Spark, and Apache Hadoop.
Beyond data integration, businesses must look for ways to make data more accessible to the end user. An integrated data approach across data-driven ecosystems and tools will help enterprises in delivering real-time insights and enrich the decision-making process.
Visualisation tools can be leveraged to bring data to life and make it easier for non-technical users to engage with it.
Utilize transparently and trusted data sources
Transparency in data sources will be critical in a data-driven ecosystem. Data quality is the biggest challenge businesses face when it comes to data-driven initiatives. Data quality can be improved by investing in data governance practices.
It is important to invest in data quality and governance to ensure that all data is clean, trusted, and accurate. Data governance can help in achieving high standards of data quality. It can also help in building data trust by making data transparent and accessible to everyone in the organization.
Data Scientist recruitment
The role of data scientists has evolved from being data-driven to data-driven. Data scientists must be more business-driven and have an impact on business outcomes. Businesses must hire data scientists who can provide value to their organization by leveraging data to provide insights and recommendations that can drive business growth.
Data scientists must be equipped with the tools and skills to integrate their findings with existing systems and automate insights for broader distribution. It is also important for businesses to invest in hiring the right talent to make the most of their data investments.
This can be achieved by hiring data scientists who are well-versed with the latest technologies and techniques in the data science field. They should have the skills and expertise to build models that can help in making better business decisions.
Conclusion
Digital transformation has redefined the role of businesses by making them more real-time, data-driven and technology-enabled. To stay ahead of the curve in this new digital world, businesses need to leverage data to drive business outcomes.
This can be achieved by always being on the lookout for data sources, leveraging AI and ML to make sense of data, building a data-driven culture, establishing real-time analytics capabilities, and using transparent and trusted data sources.
