Goto

Collaborating Authors

Chief Data Officers Face Major Challenges in Data Logistics and Management

#artificialintelligence

ET Bureau: What, according to you, is the requirement for building and refining data lakes in the cloud? Dave Murray: There's no doubt that the cloud has become the platform of choice for large data analytics projects, such as data lakes. The cloud uniquely provides a massive scale and elasticity needed to make these initiatives possible. The leading cloud providers have also brought together the necessary tools and expertise to help companies move much more rapidly toward their goals. To be successful, data analytics teams need to work closely with leaders across their companies to determine the major objectives for leveraging data.


Building the High Performing Team for Enterprise Data Analytics

#artificialintelligence

High performing teams hold the key for the successful performance of any company. Whether you have thousands of employees or just five employees, high performing teams are a must for optimal business performance. Successful analytics initiatives are no exception and are also dependent on high performing teams. However, most Data Analytics teams today are a shadow of the old MIS/BI team structure and typically reporting into the CFO function. These teams are organized around the specific IT skills that is often a combination of ETL (Extract-Transform-Loading) Developers who build and maintain a data-marts and data-warehouses, Business analysts who capture the needs of business users for operational and BI reports, and report builders who run queries and build reports.



Crafting an AI strategy for government leaders

#artificialintelligence

The city of Chicago is using algorithms to try to prevent crimes before they happen. In Pittsburgh, traffic lights that use artificial intelligence (AI) have helped cut traffic times by 25 percent and idling times by 40 percent.1 Meanwhile, the European Union's real-time early detection and alert system (RED) employs AI to counter terrorism, using natural language processing (NLP) to monitor and analyze social media conversations.2 Such examples illustrate how AI can improve government services. As it continues to be enhanced and deployed, AI can truly transform this arena, generating new insights and predictions, increasing speed and productivity, and creating entirely new approaches to citizen interactions. AI in all its forms can generate powerful new abilities in areas as diverse as national security, food safety, regulation, and health care. But to fully realize these benefits, leaders must look at AI strategically and holistically. Many government organizations have only begun planning how to incorporate AI into their missions and technology. The decisions they make in the next three years could determine their success or failure well into the next decade, as AI technologies continue to evolve. It will be a challenging period.


The Role Of Data In The Age Of Digital Transformation

#artificialintelligence

As Chief Strategy and Technology Officer at BackOffice Associates, Rex has over 28 years of technology industry leadership experience. It might be an understatement to say that today's business environment has become hyper-competitive, and the companies that aren't continuously reinventing their business -- with data at the core -- will end up watching from the sidelines while their market is disrupted. Data technologies, science and processes are rewriting the rules of business and propelling organizations toward digital transformation. Digital transformation, and the radical rethinking of how an enterprise uses technology to meet customer expectations and dramatically affect performance, is happening at a dizzying pace. In fact, IDC predicted that global spending on digital transformation technologies and services was expected to increase by nearly 20% in 2018 to more than $1.1 trillion.