Issue link: https://read.uberflip.com/i/1494715
The first challenge is a technology challenge. Data volumes are large and ever-growing. The data your organization needs to analyze exists in every format. Navigating decisions around the best way to store and manage your data can ultimately affect the agility of your business. Understanding the best tools to derive insight from the intersection of data from across your organization – whether sales and supply chain data, or Amazon product reviews, or TikTok mentions – is difficult. And finally, ensuring the use of customer data is in compliance with your organization's policies and global regulatory requirements.is complex Organizations need to be able to adeptly respond to all of these technology challenges to be data-driven. Next, there are challenges that confront the people who need to access your data. Often, the people challenges are the hardest to overcome. Different types of users have different tooling needs and skillsets. Business users want a visual experience to analyze data. Data teams want notebooks or integrated development environments. Business Intelligence users want a data warehouse, and the data science team only works with data lakes. Enabling them with the right and preferred tools to complete their work efficiently, accurately, and insightfully is essential. Challenges stand in the way of transformation 1. 3. 4. 2. Finally, there are business challenges to manage. More users desire access to more data to accelerate their decision-making. And the number of data-led projects are growing faster than budget. It's important to consider the direct and hidden costs of building on existing systems, while optimizing for the future and managing cost. Underlying all of these challenges is the complexity of managing data governance and security. In a world where data security and privacy, as well as regulatory compliance, have become integral to business growth, organizations need to be able to carefully define, monitor, and manage who has access to specific data. Access control needs to be implemented not in a siloed, piecemeal fashion but in a comprehensive and unified way across all their data, analytics, and machine learning solutions. Business leaders recognize these needs. They are taking action to modernize their data and analytics infrastructure by moving to the cloud and adopting a modern data architecture approach. With a cloud-based approach, organizations can break data silos and have seamlessly connected data stores that lead to new use cases and insights not previously possible. 3