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If data is the new business currency, then predictive analytics are the means in which organizations can take control of that currency to maximize its benefits.

Overall spending on Artificial Intelligence (AI) systems is projected to reach $79.2 billion in 2022, which is more than double the amount spent in 2019.

According to a recent retailer’s report conducted by Blue Yonder, only 14% of the 300 executives surveyed say their fulfillment locations are fully automated.

Although achieving a 360-degree view of customers isn’t a new concept by any stretch, retail organizations are still struggling to achieve this critical feat from a data management perspective.

When it comes to financial services, people’s lives can be somewhat fragmented. Depending on the situation, they might be juggling two or three different financial institutions along with several diverse financial products.

An extremely vital aspect of the banking and finance sector is their ability to manage exposure to losses & risk and to protect the value of its assets.

With the rapid growth of FinTech organizations, the banking and finance sector are chomping at the bit to figure out a way to accelerate their data initiatives.

Just like most industries, banking and finance have forever changed due to the explosion of big data and the infrastructure required for processing such data.

At Data Ideology, we have made a concerted effort to recognize and achieve high levels of gender equity in both leadership and employee level positions.

Applying for jobs can be challenging in any situation, but the task can be especially stressful for women in IT considering their underrepresentation in technology fields.

The World Economic Forum recently released the Global Gender Gap Report for 2021. The United States isn’t even in the top 20 for gender equality. Women only make up 14% of cloud computing jobs and 32% of data and AI positions.