The need for a single data architecture for hyper-growth in business
Data is the king in any business. It enables entrepreneurs to predict consumer behaviour and make informed decisions.
Today, in the modern business ecosystem today, when the world is thriving on digitisation, leveraging data has become crucial for businesses to survive.
However, a majority of businesses are unable to use the power of data extensively in their business journey.
During a masterclass at TechSparks 2021, YourStory’s flagship startup-tech conference, Pramod Rajagopal, Lead Solutions Architect, India and ASEAN, Databricks, discussed building an open data Lakehouse platform for hyper-growth for businesses and the challenges and mistakes while using data.
What is data?
Data are individual numerical facts, statistics, or items of information, translated in a form to enhance business processing and movement.
With around 600 million internet users in India, the data industry is expected to grow to $900 million by 2025. At present, businesses are leveraging data to understand customer behaviours, modify a product, or build a new product to survive in the market.
Why do businesses struggle to use data?
According to Pramod, the real challenge for businesses lies in data implementation. According to Gartner, the business value created by AI would be $3.9 trillion. However, not everyone can transform the data into production, and almost 85 percent of big data projects fail.
“Giant companies like Apple, Google, Airbnb, etc., have grown as they have leveraged the power of data. The future is here; it’s just not evenly distributed,” Pramod highlights.
Data offers a use case of complete audience experience, where there is access to personalisation engines, churn management, GDPR/CCPA compliance, sentiment analysis, and predictive analysis. It also gives advertising performance and optimisation and content lifecycle management.
But effectively leveraging data is not easy. According to Forbes, about 95 percent of businesses cite the need to manage unstructured data as a problem for their business. Forrester states close to 73 percent of company data goes unused for analytics and decision making.
“Today, most enterprises struggle with data. Disconnected systems and proprietary data formats make integration difficult and create siloed stacks, which increase data architecture complexity,” Pramod explains.
Companies are using architectural set up of data lakes and data warehouses, where raw data is in the lakes, and Business Intelligence (BI) data is in the warehouse. However, as it isn’t helping companies in a structured way, there is a need to look at things in a new direction.
What is the solution?
With over 5,000 customers globally, Databricks is one of the largest committers to the open-source ecosystem around data and AI. It envisions enabling data-driven innovation for all enterprises, irrespective of their size.
“If you could support all of your use cases with best-in-class performance on a single data architecture, why would you do anything else?” asks Pramod.
Collaborating with the best of data lakes and data warehouses, Databricks has built ‘Lakehouse’ that unifies all data, analytics, and AI workloads.
Lakehouse brings a lake-first approach, building upon where the freshest, most complete data resides. It has AI and ML from the ground up and supports multi-cloud and inter-cloud capabilities.
Built on open-source and open standards, Lakehouse supports all database management system use cases on a single platform, including data warehousing, real-time streaming, data science and machine learning, and operational workloads.
The future is AI and ML, and over time, data would emerge more powerful in running a business. Harnessing the data on a single architecture would be the key solution for business for a hyper-growth scale.
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