Data Mining

Considerations on Data Mining & Predictive Analytics

In this week, we are sharing another article on what we should care about data mining and/or predictive analytics.  For business, it is aimed to improve competitive advantages against peers in the some market.  In this article, the writer shares the fundamentals to be considered in the investment on analytics.

Original Article by Vikash Kumar:

https://insidebigdata.com/2018/11/24/data-mining-predictive-analytics-things-care/

We do believe that a basic understanding on the core of data analytics should be important for everyone in the world nowadays.

Data Mining

Privacy

Data Science & Personal Data Protection

Another day, there is another sharing of an article worth to read.  In this week, we would like to highlight the importance of privacy when doing data collections.  Even with GDPR is now applied to EU countries, but there is still room of improvement for handling data privacy.  There are lots of data analysts and data scientists’ collecting too much details including unnecessary personal data for their projects.

Article from ITPRO (itpro.co.uk)

https://www.itpro.co.uk/general-data-protection-regulation-gdpr/32372/users-told-to-ditch-onedrive-and-office-365-to-avoid

They are sharing the bad example of Microsoft for collecting personal information from Office 365.

As experienced data team, we are putting “ethical data science” as the first priority.  Masking personal information and anonymous data should be enough for most cases of data analytics.  Therefore, institutions and governments should always refine guidelines and rules on data collection to strengthen personal data protection aligned to the technology development.

Privacy

ShamShuiPo - Gentrification

Identify Gentrification and Prediction on Demand Changes

There is an article in the InsideBigData.com talking about the gentrification.  In US, the original term refers to higher income (white people) moving their homes and businesses into low-income minority neighborhoods.  However, similar situation is found developed cities like Hong Kong, you can find professionals or middle class moving into Shamshuipo (a district with lowest average household income) due to Urban renewals with newly introduced tall residential buildings.  It changes of the business environment.  You couldn’t find any café 10 years ago in this area.  However, there are 5 different “luxury” café in the district about 1047 heatares.

Original Article:

https://insidebigdata.com/2018/11/09/using-big-data-identify-gentrification-need-skilled-trades/

For facing the dynamics of a city, data is very important for businesses to identify the market trends in home building and estimating the demand for commercial space with the categorization of activities.  With the data science and data analytics, it helps to explore more possibilities with insights & prediction from data.

ShamShuiPo - Gentrification

Potential DDoS Attack from Hadoop

There is a piece of bad news for anyone using Hadoop for data analytics.  According to Radware Research team (25 Oct 2018), they have found a new botnet out targeting Hadoop clusters seeking to perform DDoS attacks.

(NOTE: Hadoop, which is an open source distributed processing framework, allows for the distributed processing of massive amounts of data and computation across clusters of computers using simple programming models).

News – Original Version

https://blog.radware.com/security/2018/10/new-demonbot-discovered/

Security teams should also look to invest in mitigation tools and services that specialize in defending against a DDoS attack.  Also, it is important to consider whether the Hadoop is necessary to connect to the Internet to reduce the chance of exposure for attack.