Apache Spark
The University of California, Berkeley’s AMP Lab, developed Apache in 2009. Apache Spark is a fast large-scale data processing engine and executes applications in Hadoop clusters 100 times faster in memory and 10 times faster on disk. Spark is built on data science and its concept makes data science effortless. Spark is also popular for data pipelines and machine learning models development. Spark also includes a library – MLlib, that provides a progressive set of machine algorithms for repetitive data science techniques like Classification, Regression, Collaborative Filtering, Clustering, etc.IMS Proschool
Explore Data & Analytics Statistics
- 61 percent of businesses that recognize the effect of data and analytics on their core business practices say their companies either have not responded to these changes or have taken only ad hoc actions rather than developing a comprehensive, long-term strategy for analytics.
- 45 percent of companies run at least some big data workloads in the cloud.
- 26 percent of businesses say data and analytics have significantly changed the nature of industry-wide competition.
- The worldwide big data market is projected to grow from $42 billion in 2018 to $103 billion in 2027.
- 14 percent of investment professionals use credit card and POS software data to derive data.
- 55 percent of North American businesses have adopted big data analytics.
- Customer/social analysis is considered the second most important big data analytics use case, followed by predictive maintenance.
- By 2025, the amount of the global datasphere subject to data analysis will grow by a factor of 50 to 5.2 zettabytes.
- Analytics leaders are nearly twice as likely as others to report enacting a long-term strategy to respond to changes in core business practices.
- Only 7% of marketers surveyed report that they are currently effectively able to deliver real-time, data-driven marketing engagements across both physical and digital touchpoints.
Check Out Data & Analytics Tools
Recent Blogs on Data & Analytics
- Top 5 Benefits to Centralized Data
- Winning strategies for Data Governance maturity
- Top 5 performance best practices with Snowflake
- Part 2: How the Snowflake Cloud Data Platform transforms organization?
- Data Warehouse: Keys to Success
- Why do you need a Data Strategy now more than ever?
- Power BI Download Options: App vs MSI
- Data Governance: Lessons learned for best practices
- Launching A Master Data Management Program: The Keys to Success
- Part 1: How the Snowflake Cloud Data Platform transforms organization?