Data and AI Experts Share Predictions with Databricks: What the Future Holds for AI, Big Data and Analytics
SAN FRANCISCO--(BUSINESS WIRE)--Jan 15, 2019--2018 was an unmatched year for the tech industry, with several sectors including artificial intelligence (AI), big data and analytics garnering increased investment and innovation. With 90 percent of enterprises already investing in AI technologies, the steady momentum shows immense opportunities for growth – for both technology providers as well as the customers they serve. Databricks, the leader in unified analytics and founded by the original creators of Apache Spark™, sees 2019 as the year that more companies solve the world’s toughest data problems that have hindered AI initiatives across industries. This perspective is shared by data thought leaders who advise on AI, big data and analytics trends that inspired them in 2018, and those on the horizon for 2019:
Solving the world’s toughest data problems starts with bringing all of the data teams together within an organization. Data science and engineering teams’ ability to innovate faster has historically been hindered by poor data quality, complex machine learning tool environments, and limited talent pools. Additionally, organizational separation creates friction and slows projects down, becoming an impediment to the highly iterative nature of AI projects. Much like in 2018, organizations that leverage Unified Analytics will have a competitive advantage with the ability to build data pipelines across various siloed data storage systems and to prepare labelled datasets for model building, which allows organizations to do AI on their existing data and iteratively do AI on massive data sets.
For more information about Databricks’ Unified Analytics Platform, visit www.databricks.com.
Databricks’ mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the original creators of Apache Spark, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership. Databricks, venture-backed by Andreessen Horowitz, NEA and Battery Ventures, among others, has a global customer base that includes Viacom, Shell and HP.
Apache, Apache Spark and Spark are trademarks of the Apache Software Foundation.
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