Realizing the Value of Big Data through Data Quality

In modern data architectures, we’re increasingly moving from single node design systems to distributed architectures using multiple nodes often spread across multiple databases and multiple continents. Such architectures bring many benefits (such as scalability and resiliency), but can also bring a lot of pain if incorrectly architected.

In today’s corporate finance departments, the pressure to do more with less is greater than ever. The most successful finance teams partner with other lines of business to drive growth through data-driven insights, using advanced analytics and predictive models. But translating insights into real-time actions requires real-time analytics that can’t be achieved with traditional business intelligence solutions and dashboards. To unleash the full power of your finance data, you need a new approach.

Organizations that operate worldwide typically need to manage data both locally and globally. Local business units and subsidiaries must address region-specific data and accounting standards, regulations, customer requirements, and market drivers. At the same time, corporate headquarters must share data broadly and maintain a complete view of performance for the entire enterprise. For many global firms, data is the business. They need state-of-the-art data management just to remain innovative and competitive. Hence, multinational businesses face a long list of new business and technical requirements for modern data management.

Today’s most successful organisations are utilising data to drive accelerated growth. They are each on a journey towards greater data maturity, increasing the value of their data and deepening their insights as they go. However, the rapid growth of analytic solutions has not successfully transformed every business into a data-driven powerhouse – yet. So how can you ensure the route you take to AI maturity is a successful one? As with any endeavor, your company will face obstacles as you strive to transform into a data-driven organisation. To succeed, it’s important to evaluate where you are today, the challenges that lie ahead, and what exactly “ahead” means for you and your team.