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" ... However, despite the attention paid to the Fed and the often historically positive stock market reaction, they see non-farm payrolls as being a key datapoint for markets too, though not necessarily as positive for stocks. Ironically, bad payroll data during a positive period can be positive for stocks as it may lead investors to factor in a rate cut, more than offsetting negative growth expectations that may already be perceived by the market. ... "
" ... One final datapoint should make executives happy: The number of surveyed executives who expect declining growth by 2022 is zero. ... "
" ... Real-time high-resolution location data is a particularly dangerous datapoint for companies to sell given that it can be used by bad actors for everything from stalking to committing robbery, rape and murder or by foreign actors to map out national security. Whether identifying when a target is waiting at a bus stop alone or simply mapping her daily pattern of life to determine her most vulnerable moments in a typical day, location information is extremely sensitive and one of the classes of private data that most connects the digital world to our physical one. ... "
" ... Shariq: One of the biggest challenges we realized is around conversion of source documents. A lot of the data that we collect is publicly available through regulatory filings documents from sources like the Edgar-SEC. However, just because data is available does not make it easily accessible. These regulatory documents are often in PDF form which we know can come in either text or images-based form. PDF’s are great for human consumption but not for machines to parse. We can write a program to parse a PDF file to access meta-data and text content but we may not be able to access formatting which is a key element to ensure we maintain datapoint relationships such as correlating a line item in a row to a particular time period in a column. Therefore, we first convert documents into machine parsable form. This is where it can get really tricky. Given we process documents from over a 100 markets, the level of variance we see from market to market is very high. There’s often variance even within a market. There isn’t a single tool available on the market that can handle conversion challenges that we encounter across all of the markets that we collect. So, we’ve built a pretty robust conversion API that leverages a number of solutions underneath from commercial, open source to homegrown options. We also have a patent pending on a solution to help with table parsing on international filings documents. All of these solutions sit behind an easy to consume API. We’ll continue to innovate and improve our conversion capabilities. ... "
" ... This represents a philosophical tradeoff. On the one hand, computer science students are taught to collect every datapoint they can at the highest resolution they can and to hoard it indefinitely. This extends all the way to things like diagnostic logging that often becomes an everything-or-nothing concept that has led even major companies to have serious security breaches. On the other hand, disciplines like library and information science emphasize privacy over capability, getting rid of data the moment it is safe to do so. ... "