Separating Signal from Noise
One of the biggest problems posed by big data is separating the signal from the noise, or cutting through all the data to find insight and value. The 2013 IBM Institute for Business Value study surveyed 900 business and IT executives from 70 countries to assess how they’re converting data into meaningful insights – and results.
Data governance, filtering, machine learning and cognitive computing are all part of the story, as is faster processing. However, some needs are less tangible, like building a culture based on analytics.
The study will be released on October 29, and should provide some valuable information on how executives are addressing the challenge with actionable recommendations.
The very next day, on Wednesday, October 30 at 1 PM ET, Dr. Steve Buckley, IBM Business Analytics & Optimization Applied Research Leader, will join our #ibmblu twitterchat to discuss some of the study results, and how many organizations are separating signal from noise.
We’ll wrap our conversation around these questions. Starting thinking of your answers, and be sure to join us. [UPDATE: You can now view the Study results.]
Q1 How do you cut through all the "noise" posed by various big data sources?
Q2 When & how can analytics begin to drive value?
Q3 How do organizations overcome bad data quality or extraneous data?
Q4 How does the abundance of new data create a new equation for business – and even DBAs?
Q5 How can speed and hardware separate noise from signal in data?
Q6 How does one augment capabilities to read new signals – voice, text, video for big data?
Q7 What are the technology needs to better distinguish noise vs signal?
Q8 As noise continues to increase, what’s next?