3 Reasons Companies Advance Their Data Journey to Combat Economic Pressure
By Danny Vally
Have you updated your organization’s data journey lately? We are living in the Zettabyte Era, because the volume, velocity, and variety of data assets being managed by companies are big and getting bigger.
Data is getting more complicated and siloed. Today’s data is more complex than the data a typical business managed just twenty years ago. Even small companies deal with large data sets from disparate sources that can be complicated to process. Each data set may have its own unique structure, size, query language, and type.
The types of data are also changing quickly. What used to be managed in spreadsheets now demands automated systems, machine data, social network data, IoT data, customer data, and more.
There are real economic advantages for companies that take advantage of the data opportunity by investing in digital transformation (often starting by moving data to the cloud). Companies that take control of data outperform the competition:
- 40% more revenue per employee
- 50% higher average net income on revenue
- $100M in additional operating income annually
Common data journey scenarios that motivate data-driven investments include:
- Understand and predict customer behavior in real-time
- Cut costs and free up resources with simplified data analysis
- Explore new business models by finding new relationships in data
- Eliminate surprise and unnecessary expenses
- Gather and unify data to better understand your business
A data strategy is more than a single tool, dashboard, or report. A mature data strategy for any business includes a roadmap to plan the company’s data architecture, migration, integration, and management. Building in governance planning to ensure data security, integrity, access, quality, and protection will empower a business to scale.
That roadmap may also include incorporating artificial intelligence and machine learning, which unleashes predictive analytics, deep learning, and neural networks. While these once were understood to be tools available only to the world’s largest businesses, AI and ML are actually being deployed at even small and midsized businesses, with much success.
We work with organizations throughout their data journey by helping to establish where they are, where they want to go, and what they want to achieve.
A data journey usually starts by understanding data sources and organizing the data. Many organizations have multiple data sources, so creating a common data store is an important starting point. Once the data is organized, we can harness insights from the data using reporting and visualization, which enables a real-time understanding of key metrics. Ensuring data governance and trust in sharing data is another important step, which is often supported by security. Lastly, advanced data can use artificial intelligence and machine learning to look for data trends or predict behaviors and extract new insights. By understanding where your organization is in its data journey, you can begin to visualize its next step.
- Downloadable PDF: Set Your Data Retention Policy up for Success
- Data Mesh Architecture in Cloud-Based Data Warehouses
- Cloud Migration and Cloud Services
- Using Data to Improve Patient Outcomes
- Databricks whitepaper: Data Warehouse meets Data Lakes