Best Data Analysis Quotes

"Failure is the most information-rich data stream on planet Earth."

"The essence of good science is whenever you see some data and an inference, ask yourself: How might that inference be wrong? How else might we account for those data?"

"The best predictor we see in the data of whether people are happy or not is whether they're satisfied or happy with their relationships."

"The data collected by Neuralink will be fed to an artificial intelligence, it will start recognizing patterns and finding things that a single human cannot see."

"Most distributions are not normal distributions but Power law distributions."

"I'm all about data; I'm not into CNBC headlines and just summarizing crap. I want to give you the stuff that nobody else is giving you."

"Also it's possible that we're not using magic power so much as looking at data."

"Don't take the data at face value; always ask yourself, is this the expected result?"

"Data, data, data, man. There is an answer, and if you have the discipline of not tying your identity up into an answer and you stay open to new truth, that's powerful."

"When scientists use Bayesian inference, you can start with different priors...but as you continue the Bayesian process and as you continue to pull in new data, they're going to be converging on common answers."

"If you just lazily extrapolate all the women and all the men at a certain age and don't take into account job experience, the gender wage gap does exist. But if you take in women that study the same stuff as men and are in the workforce at the same time as men, they actually earn a hundred six cents of the dollar more."

"The truth requires you to say, 'Maybe I'm wrong.' Is this data right? What are my opponents saying, and is there any validity to it?"

"There is every reason for us to be confident, there is every reason for us to look at the data; we've done this before, and we'll do it again."

"The importance of keeping clear lines of communication open with really good data is crucial, as they are the boots on the ground in the fight against this virus."

"The long game here is not to make money selling kits, although the kits are essential to get base-level data. Once you have the data, the company does actually become the Google of personalized healthcare."

"This isn't financial advice, but I've been analyzing financial data."

"The point of going through science and data is not to be right; it's to get closer to the truth with every passing iteration."

"Data Analysts deal with data handling, data modeling, and reporting."

"Business analytics is the process of transforming data into insights that support, improve, and/or automate business decisions."

"Imagine... based on your Facebook patterns, it figures out that you're pre-diabetic."

"It's not a matter of being right or wrong, the data will either support or refute the hypothesis."

"So basically what you're going to do is take a bunch of crappy unorganized data and you are going to organize it in such a way that not only does it make sense, but you can make business decisions based on it."

"You're only going to fix the problem by looking at the data, finding out what are the challenges, fix many of these challenges, and realizing you can't fix everything."

"You've got to stop believing that this is the end of the world. That's not what the data shows us."

"Insight has given us an incredible amount of raw data, including a fascinating comprehension of Martian weather patterns."

"By the end of Day 1, you will have transformed local data, web data, and a little bit of curiosity into stunning visual analysis and business insights."

"Pivot tables have been the most important end-user analysis tools in data since the early 90s."

"The only success story it looks like here is California. That's not actually true, right? I have a lot of success stories."

"Once you have this data...turning it into great information that you can use and directly apply, that's where the real power lies."

"The empirical and rational hypotheses... we can't orient ourselves by the data alone because there's an infinite plethora of data."

"There is a massive amount of data on things you can do with regards to police behavior to decrease criminality, and it is not putting a ton of police in there."

"The goal of a procedure like factor analysis is useful insight."

"The truth is also that Six Sigma is beyond analyzing data. While Six Sigma professionals are skilled at interpreting data, a software like Minitab is vital in determining the real underlying cause of problems within a process, which makes problem-solving a much faster and easier process."

"A run chart displays how your processed data changes over time and can reveal evidence of special cause variation that creates recognizable patterns for distinguishing the reasons of variation."

"My goal is unbiased. I want to give you the data so you can create your own analysis and understand what's happening."

"Let's not take our eye off the ball just because the numbers are flattening."

"Data analysis is defined as converting raw data into useful information for decision makers."

"Data analysis is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making."

"Data analysis is taking raw data and creating useful information."

"Charts are absolutely data analysis also. We're taking a bunch of raw data creating useful information."

"Data, data, data. I can't make bricks without clay." - Sherlock Holmes

"Data is basically a collection of facts or information, and through analysis, you'll learn how to use the data to draw conclusions and make predictions and decisions."

"We are very close to the point when we have enough understanding of biology and enough data on people and enough computing power to really hack humans."

"In the data space... asking the right question is one of the best things that you'll do for your data project."

"This is something you could present to a business person and say, 'Hey, look at this data. This is from the past year. Let's target our ads at this time.'"

"We can use this chart to help us really understand our data and give key insights."

"Quantitative is like running the numbers. What does the hard math say?"

"Simpson's paradox is a paradox in statistics where when you look at things in aggregate as opposed to separately, you get completely opposite results."

"Our data sets are full of disclosure...over these next five years we get all kinds of fantastic technologies brought out to us."

"Look at the data without any bias. That's all I ask."

"It's now easy to take algorithms and embed them into computers and gather all that data that you're leaving on yourself all over the place, and know what you're like, and then direct the computers to interact with you in ways that are better than most people can."

"I am data-driven. The data is compelling, including 360-degree polling data, that said people would have changed their vote had they been exposed to information that was systematically suppressed."

"As a scientist, my job is, I see something weird, my job is to figure it out. We go get more data, we come back to it. We live for weird stuff."

"Genome testing gives us way more data so that way we aren't flying totally blind."

"I made a mistake. Focused on big picture; big picture made of little pictures. Too many variables, can't hide behind statistics, can't ignore new data. My responsibility. Need to go. Running out of time."

"In the long run, historically that's what the data suggests, that's what matters for the housing market."

"Rather than writing down the features ahead of time, we're going to learn the features directly from the data."

"I initially set out to justify this worldview that I had cultivated for myself, and over time, when you actually look at the data and you dig into it, you find yourself at a crossroads. It's like, well, either I can accept that the data is telling me something different, and I should be open to maybe the fact that I'm wrong, or you double down and you say no, the data's wrong, this is actually wrong."

"When we regress standardized values, some interesting things become apparent that are kind of happening under the hood."

"Standardized values can be very helpful in that regard."

"We've got some actual data... that often provides somewhat of a basis for future anticipated earnings."

"Correlations are a great way to get an idea of how different variables relate to each other in a dataset."

"The reason why the Mighty Fall is they do not look at the data that doesn't make them happy. They don't have the guts to do it."

"We shouldn't be anti-intellectual and we should look at the data provided."

"We cannot equate UFOs and aliens. The government has been very clear on this... No one in the government is talking about aliens... It's very important to keep that separate. Let's keep our eye on the ball; let's try to figure out what these things are, gather all the data, let science take a good look, and then take it from there, one step at a time."

"The key idea of deep learning is to learn these features directly from data in a hierarchical manner."

"The Cow was joined by The Koala and The Camel. And just like that, they had data on three separate LFBOT events. They could start hunting for patterns."

"Sequential processing can be useful from medical signals to EKGs to prediction of stock prices to genomic or genetic data and beyond."

"To find conviction in a trade, I need to have the data to support the actions that I'm taking."

"The great thing about data is, the more years you have to see if something's working or not, the proof is in the pudding. This doesn't lie. This is numbers."

"This ability to hack human beings, to go under the skin, collect biometric data, analyze it, and understand people better than they understand themselves, is the most important development of the 21st century."

"This data-driven approach requires input from a wide variety of sources."

"It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts."

"Data, numbers today, we're going to break down the numbers for World of Warcraft to get an overall picture of the game's health."

"The power of BigQuery is its ability to run SQL queries over terabytes of data in seconds."

"There's actually lots of manufacturing jobs that are being made here in the U.S. They're just not assembly jobs. They are data analysis jobs, engineering jobs."

"Solving problems is about observe, collecting data, building models, then verify and observe again."

"It's worth noting that if the data you collect is unrepresentative, then the conclusions you will draw will be similarly biased."

"I think there are a number of ways to combat misinformation. One of them is accurate information and truth and data."

"Every piece of data is uncertain. We don't put too much stock in any one month's data. We're looking at longer-term trends and certainly, as we assess the trend over the longer term, we feel like we are seeing a strong and accelerating recovery."

"Every single model is only as good as its assumptions."

"Overall, I was quite impressed with the data that the 645 collected."

"My confidence isn't in the experts; my confidence is in the evidence and data they cite that makes them experts."

"Mitigation does work the reason we know it works is the question that was asked about the numbers that why they came down of the projections."

"Pandas is great for a wide variety of steps in the data science process."

"We're now introducing the Shopping Graph, our most comprehensive data set for billions of products and the merchants that sell them."

"How do you eliminate the mundane so we can solely see the weird and unexplained core that seems to be in all of this with actual solid scientific data sets that will let us try to determine exactly what this is?"

"Data-driven decisions. The data doesn't lie, the data tells a story. Follow the data, tweak your behaviors by the data, and sure, there's some hunches, luck in there as well."

"I just saw this statistic from the Washington Post showing that from 2008 to 2018..."

"The numbers don't lie, they are what they are, and if you try to disprove your hypothesis enough, you can actually get close to something very few people care about nowadays: an objective truth."

"Everyone wears jeans but no two people will wear them exactly the same way."

"Interesting data and trends under critical trends on the Johns Hopkins site."

"The media has been lying to you, and because you've never really heard the actual stats and data."

"What is this potentially mean? Well, the data is actually telling us that we might be at a leading indicator inflection point."

"Google Analytics is a piece of software that gives you lots and lots of data around how people are behaving on your website."

"Decision intelligence... it's all about the data... it's taking off."

"Machine learning gives us the ability to learn things about the world from large amounts of data that we as human beings can't possibly study or appreciate."

"We understand reality, we look at the numbers."

"Well, let's gather the data before implement policy."

"The truth though is it really depends on the problem. I wouldn't focus so much on which algorithm to use as I would on understanding the questions first that you're trying to answer."

"Even the multivariate adjusted data ends up telling the same story."

"We've all seen this chart before. This is real growth, not hype."

"Mistakes are the most information-rich data stream you will encounter, so go make some."

"The on-chain activity is not matching, and that's the biggest thing."

"Adding more data leads to a virtuous cycle of improvement."

"Anytime you go from raw data and you create useful information to help you make decisions, you've done data analysis."

"Spaceflight is hard and can be unforgiving, so you try to look at minute changes in data."

"The data is real; now let's figure out what it tells us."

"There's been several plateaus in the decline."

"It's not the data that falls in line that's so interesting. It's the spot off the graph that you want to understand."

"It's what we can extrapolate from the data and it's what we can get from the data to understand about our target market their needs etc that's where the real wind comes from keyword research."

"Sorting and filtering are useful when you're doing analysis on a bunch of data."

"All these things are data points in the graph that hopefully is trending upwards to Mars."

"Interview prep is an important part of becoming a data analyst. Very few people are naturally good at interviewing."

"So, if you want to isolate and find out how many people are charging between 55 and 77 dollars a night, you scroll down and see that there's 8 rentals at that price point."

"AI encompasses many fields including machine learning, which processes large amounts of data to derive a pattern and predict outcomes."

"Real answers only come when you have real inquiry with real tools to measure and analyze real data from The Real World."

"When confronted with a vast number of observations, a first step to understanding is categorization."

"There's a 95% probability that this interval contains the true mean difference between the two call centers."

"You're sitting on a gold mine of data of people that would consider it."

"The three key factors you have to look at: data, algorithms, and talent."

"Rationality should be you start with the data and you work for the conclusion. Rationalization is you start with the conclusion you like and then you go backwards and construct a seemingly rational justification for it."

"It's a really exciting discovery, to hear about something you would discover in old data."

"Translation isn't that big of an issue if we can accurately assess the data."

"Revelation of new data invariably raises new questions."

"Our target goal is 10%. We don't try to make a lot of money in one load. We try to make steady money throughout the year."

"What we really want is, if I give you two pictures of the same person, I want the vector to be similar."

"You can test a hypothesis ... what happens if ... our data, may be crappy, but it's still data and it allows you to go further with 100,000 people, 50,000 people, 500,000 people."

"Unsupervised learning groups the data based on some measure of similarity."

"All of these people are using the same data, but as you can see, the outcomes are very different."

"It's not a formula that you put the data in and then you get an answer and everybody comes to the same decision."

"A good component about going through these documents is going to be just sifting through at random raw data and then finding threads."

"Data scientists analyze and interpret complex data to help organizations make better decisions."

"Clustering: taking an automatic grouping of similar objects into sets."

"Pandas library is pretty widely used as a data frame setup."

"You start looking at all these numbers and all this text and you get down here and you say oh yes."

"Your niche will find you after you've collected enough data on what's working."

"But wouldn't it be nice to just be able to manipulate the raw data, relatively simple though it is, to just answer questions about the data?"

"What does the data tell us about what our future world might look like?"

"AI has become more sophisticated, algorithms have become more capable at drawing effective conclusions from the data to which they had access."

"The algorithms process the data to make predictions. Roughly speaking, we're all working with the same data, but you'll have some people with better algorithms and some people with worse algorithms."

"The data simply does not back up their claims."

"In cases that are this complex and with so much data floating around, you cannot solve the case unless you have a very good structure built up front."

"State the coordinates of the outlier, there's one point there which doesn't fall into the general pattern of this scatter graph."

"Knowing that the data you want to pay attention to is inflation."

"The incorrectness of data, uncertainties of the future, and irrationalities of markets, complicate the work of the analyst but they do NOT nullify it."

"Visualization is important because visuals can help data analysts understand and explain information more effectively."

"Being strategic is key to staying focused and on track. It helps data analysts see what they want to achieve with the data and how to get there."

"Power BI helps you get insights from your data."

"The power that the DAX gives you and being able to write these measures really makes a big difference to the sort of reports that you could be producing."

"And the beautiful thing is, you can then go and look at my sources, look at the data sets that I used, and you can interrogate them."

"So now we can actually do what we first set out to do and use this data to determine what the most popular or homebrew packages are."

"One of the few analysts out there that also sticks to the data sticks to the data leaves all the all the all the other stuff to the side and I think does a good job a great job managing emotions."

"The validity of the test kind of depends on the data that you sample to begin with."

"There's a negative and positive spike across various channels."

"So both traces always move together horizontally."

"But in essence, we built our dashboard based on the data model that had tables from Power Query, relationships, and DAX formulas."

"These numbers are telling us that we are still each day learning about the full effects of this virus."

"Take all of the data that we have and have more analytical and predictive power."

"We can actually quantify the extent to which this does work, what we know and don't know."

"Always take data very seriously; it can give great insight into the future."

"Give me the data so I can have a look and understand it better."

"Cut through the bs and share exclusive hard data on the Dallas housing market so you can understand whether this is the year in 2022 to buy or to wait."

"Whenever good philosophy tends to line up with good number crunching usually I'm all in."

"Retain the artsy side of being a creator with the data-driven aspect of being an entrepreneur."

"Consider the limitations and biases of your data when analyzing it."

"You choose your plot type based on the question you're answering and the data types you're working with."

"The fact that you can ignore almost all the data and still find out what's going to happen next in the life of this macroscopic system is a real objective fact about the system."

"I care about points on a graph and where that line is going."

"If you can look at a database of 45 million people who voted in this election and you can't draw some conclusions from that, you're doing this wrong."

"This is the data I've been dreaming of for 20 years Patty, and it's changing everything in law enforcement."

"We have brokerages, they have prime brokers... this could be one particular scenario of like hey they're trying to get that business, they're trying to impress the hedge fund."

"It's just a matter of how long you're willing to wait to get the data."

"Okay, over the April 10th there were 67,000 diagnosed cases of COVID in the United States... we are not surging, we are completely flat."

"We need to make sure that we form valid, coherent, and robust perceptions by reviewing and assessing all available data."

"So if you can use cell phone tracking to find people who are going in a short period right after the election the few days after the election to 10 or more drop boxes that needs to be investigated."

"There's no shortcut to it, you will go into charts, you will study, you will look at old data, you will back test."

"It people shake their head and say it can't be so until you know you look at the data of the difference it makes."

"So what's the conclusion on all this? Well, I mean if you look at the data and you look at history and history tends to rhyme doesn't it always have to repeat but tends to rhyme."

"Stats rarely tell the whole story. So, you've boiled down your search to a few companies based on numbers, the ones that you've learned in this presentation. You've eliminated a lot of the bad apples."

"Until you stop it, you gotta look at the power numbers. Let's figure out how to stop this stuff."

"The answer to your problems is always right in front of you somewhere in the data."

"A man who quickly discovers exactly how the swamp operates."

"Look at the facts, look at the data, look at the fact that we have one of the lowest case fatalities in the world."

"Palantir became the government's go-to company."

"I was very critical based on the empirical data."

"We should not only look for the things we know, we should also look for things that don't fit into the data, that look different, that look anomalous."

"We can actually reduce this down to a workable data set."

"Empirically provable data shows Marxism is a failure."

"If you can simplify your understanding of the data, follow this structure, report the data accurately, and use the correct grammar and vocabulary, then you have a very, very good chance of dramatically improving your score."

"There's never one answer in optimization. It's about analyzing data, identifying issues, and finding solutions that work without breaking the game."

"Data analysis: that's where you look at raw data, organize it in some way, and come to some conclusion."

"You just can't even believe because the numbers are moving so fast."

"Overall, the process gives you a smoothed out version of the original data."

"One thing you have noticed is our set sentiment amplification scores have been skyrocketing."

"You need fact, you need data, you need information."

"So are we missing a trick from Africa data? I think we are."

"The whole point of this series is that if you are trying to apply for a data analyst job, by the end of the series you should have an entire portfolio or at least a really good start at a portfolio to show a potential employer."

"This data just taken by itself makes an argument for hey, maybe the worst might be behind the economy and things are picking back up again."

"There's value in data, but not a single data point paints an actual or fair picture."