<p style="text-align: justify">Machine learning is not just for Artificial intelligence and predictive analytics. Today, it encompasses a wide array of computer generated information that can be used to automate the entire value chain of managing, storing, processing and analyzing data. Of these, Personal data is the most prized asset that bears the brunt of poor security and cyber-crimes. In this risky ecosystem, secured Machine Learning algorithms would safeguard all the Personal Data Management and Privacy benchmarks.</p>
<p style="text-align: justify"><em>With the Analytics from machine learning-powered software becoming more and more sophisticated, we can expect ML-driven embedded automation cutting through all the noise in the Big Data industry.</em></p>
<p style="text-align: justify">If you are learning from Analytics Training Bangalore courses online, here is what you should focus in the Personal Data Management and Privacy space.</p>
<p style="text-align: justify"><strong>Data Cataloguing</strong></p>
<p style="text-align: justify">Using Predictive Analytics running on Machine Learning algorithms, modern data management tools can properly catalogue and categorize data automatically. These can be applied to data sources, data sets, tables and personal data fields. Personal data such as home address, security identification numbers, credit card information, insurance and legal aspects can be protected by categorizing each data into domains based on compliance risk and quality levels.</p>
<p style="text-align: justify">In the foresight, data cataloging not only helps to safeguard data, but also help to enrich cross-relational information based on various forms of analytics and machine learning intelligence.</p>
<p style="text-align: justify"><strong>Data Domain </strong></p>
<p style="text-align: justify">By nature, personal data related to Finance, email address, smartphone apps, and social media information are most prone to privacy breach and hacking. Data domains in such aspects can be recognized and fortified with additional layers of identity management and user authentication tools automated using ML algorithms.</p>
<p style="text-align: justify"><strong>Metadata</strong></p>
<p style="text-align: justify">With the recent anniversary of GDPR, we have understood how top data aggregators have forced personal data management guidelines into oblivion. If the GDPR wasn’t established, all data aggregator would have continued to sell personal data information to highest bidders at a premium. The losers here – the customers who continue to put data on the burner, thinking the aggregator and search engines would continue to provide great experience and never compromise on the privacy. How untrue!</p>
<p style="text-align: justify">With ML automating the Metadata management for GDPR compliance, things have come under scanner of the data regulators. Today, you will hear and read about data police fining and penalizing data collectors for billions of dollars in the European courts.</p>
<p style="text-align: justify">But, it’s not that easy as it is made out to be.</p>
<p style="text-align: justify"><em>All Data regulators are still facing the common, age-old challenge. They do not hire enough data scientist and analysts to skim all that personal data privacy breach complaints rising from around the world! </em></p>
<p style="text-align: justify">With the lack of enough talent in the industry, managing Metadata Personal information has become ambiguous, often risking being turned into curse than a cure for businesses. Today, the price of being inaccurate and slow is too big to pay for businesses and analysts. <strong><em>With BI teams hiring from analytics training Bangalore, Personal data management is only going to get better and smarter.</em></strong></p>

Making Personal Data Management Accurate and Smart
