Semantria
Semantria is a tool that can collect posts, tweets, and comments from social media channels. It uses natural language processing to parse the text and analyzes customers’ attitude. This way, companies can gain actionable insights and come up with better ideas to improve your products and service.Octoparse
Explore Data & Analytics Statistics
- The big data industry will be worth an estimated $77 billion by 2023.
- Nearly 50 percent of businesses say big data and analytics have fundamentally changed business practices in their sales and marketing departments.
- 21 percent of investment professionals use web traffic to derive data.
- Analytics leaders are nearly twice as likely as others to report enacting a long-term strategy to respond to changes in core business practices.
- Customer/social analysis is considered the second most important big data analytics use case, followed by predictive maintenance.
- Through 2019, 90% of large organizations will have hired a CDO, but only 50% will be considered a success.
- In the banking sector, investments in big data analytics were estimated at $20.8 billion in 2016.
- 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.
- 29 percent of investment professionals use expert networks to derive data.
- In 2025, the IoT data analyzed and used to change business processes will be as much as all of the data created in 2020.
Check Out Data & Analytics Tools
Recent Blogs on Data & Analytics
- Why do you need a Data Strategy now more than ever?
- The Value of Data Management
- Don’t Let Technical Debt Bankrupt Your Data Foundation
- Finance Data Management & Governance Importance
- Power BI Reports vs. Dashboards
- Snowflake Delivers a Single Data Experience Across Multiple Platforms
- How to get started with Data Governance
- Mothers in Tech: Design your Own Work-Life Balance
- Enterprise Data Strategy: What is it? And why is it important?
- Launching A Master Data Management Program: The Keys to Success