WHY IT MATTERS: Digital Transformation

If you collect email information at the point of sale for your loyalty program, you can import store transactions directly into AdWords yourself or through a third-party data partner. And even if your business doesn’t have a large loyalty program, you can still measure store sales by taking advantage of Google’s third-party partnerships, which capture approximately 70% of credit and debit card transactions in the United States. There is no time-consuming setup or costly integrations required on your end. You also don’t need to share any customer information. After you opt in, we can automatically report on your store sales in AdWords.

A study published today suggests your Apple Watch could help detect and track serious heart conditions. According to CNET, researchers from the University of California, San Francisco worked with the app Cardiogram on the Health eHeart study, gathering cardiovascular data from 6,158 people who used Apple Watches. They tested whether the watches were able to …

An oil refinery is an industrial cathedral, a place of power, drama and dark recesses: ornate cracking towers its gothic pinnacles, flaring gas its stained glass, the stench of hydrocarbons its heady incense. Data centres, in contrast, offer a less obvious spectacle: windowless grey buildings that boast no height or ornament, they seem to stretch to infinity.

Also read: http://www.economist.com/news/leaders/21721656-data-economy-demands-new-approach-antitrust-rules-worlds-most-valuable-resource 

Instacart is excited to announce our first public dataset release, “The Instacart Online Grocery Shopping Dataset 2017”. This anonymized dataset contains a sample of over 3 million grocery orders from more than 200,000 Instacart users.

For each user, we provide between 4 and 100 of their orders, with the sequence of products purchased in each order. We also provide the week and hour of day the order was placed, and a relative measure of time between orders.

Consumer-goods companies have begun to capture value by applying digital tools to manufacturing. Here’s a look at how they’re doing this today--and how they might do so tomorrow.

Alphabet’s artificial intelligence outfit, DeepMind, plans to build a blockchain-style system that will carefully track how every shred of patient data is used. The company, which is rapidly expanding its health-care initiatives, has announced that it will build a tool that it calls Verifiable Data Audit during the course of this year. The idea: allow hospitals, and potentially even patients, to see exactly who is using health-care records, and for what purpose. By logging how every piece of patient data is used, the company hopes to leave behind an indelible audit trail.

100 million rides and runs, 220 billion data points visualizing the best roads and trails worldwide.

Big data’s potential just keeps growing. Taking full advantage means companies must incorporate analytics into their strategic vision and use it to make better, faster decisions.

• 70% of retail decision makers globally are ready to adopt the Internet of Things to improve customer experiences.
• 73% of retailers rate managing big data as important or business-critical to their operations.
• 78% of retailers say it is important or business-critical to integrate e-commerce and in-store experiences, so an omnichannel experience is delivered to every customer.
• 87% of retailers will deploy mobile point-of-sale (MPOS) devices by 2021, enabling them to scan and accept credit or debit payments anywhere in the store.
• 90% of retailers will implement buy online, pickup in store by 2021.

With the explosive growth of online activity and social media around the world, the massive amount of real-time data created directly by populations of interest has become an increasingly attractive and fruitful source for analysis. Despite the limitation that social media users in the United States are not a random sample of the US population [7], there is a wealth of information in these data sets and uneven sampling can often be accommodated.

Indeed, online activity is now considered by many to be a promising data source for detecting health conditions [8, 9] and gathering public health information [10, 11], and within the last decade, researchers have constructed a range of public-health instruments with varying degrees of success.

Fine-tuning these algorithms is key to improving large-scale analysis of social media, whether the goal is to measure the caloric content of a tweet or to find the next developing news story. These technologies represent new ways of finding and understanding the conversations we're having as a country -- chatter that is increasingly moving online.

Explore the fitness and workout trends of Fitbit users, and get exercise advice from the experts in this comprehensive, interactive infographic. At Fitbit, we geek out about workouts. Feast your fitness-loving eyes on the first ever Fitbit Health & Activity Index that identifies some of the most popular activities, shifts in workout trends, and ways to stay motivated.

The diminishing effectiveness of conventional advertising and the rise of social media have led more and more brands to embrace content marketing. More and more companies are seeing themselves not just as advertisers, but as publishers, launching digital newsrooms, podcasts, and other forms of branded content in order keep their brands, perspectives, and value propositions in front of customers.

“During the 100 days before the relationship starts, we observe a slow but steady increase in the number of timeline posts shared between the future couple.”

Only Facebook could create Safety Check, not because of resources as you might expect, but because Facebooks lets employees build crazy things like Safety Check and because only Facebook has 1.5 billion geographically distributed users, with a degree of separation between them of only 4.74 edges, and only Facebook has users who are fanatical about reading their news feeds. A small team couldn’t build a big pipeline and index, so they wrote some hacky PHP and effectively got the job done at scale.

This paper details how Facebook build Safety Check

Training materials obtained by the Electronic Privacy Information Center show Palantir plays a role in a far-reaching customs system

Now a new breed of software applications is reshaping sales force management. Their common characteristic: Using digital data exhaust, which is the data generated from the regular activities of a sales force or their customers, to change the behaviour of frontline sales representatives in ways that dramatically improve sales productivity and effectiveness.

Onfido delivers next-generation background checks, helping the world’s most innovative businesses verify anyone, anywhere.

Scott Crouch and his college buddies built Mark43 to help police do their job more efficiently and effectively.

Twenty-four hours a day, across more than sixty free product “platforms," Google is storing, indexing, and cross-referencing information about the activities of a billion people. What are the 30,000 prodigies at Google, Inc. doing with all that data?Continue Reading…

What is the weather today? You don’t need to be a meteorologist to answer this question. Just take a look outside the window. Macroeconomists do not have this luxury. The first official estimate of GDP this quarter will not be published until the end of July. In fact, we don’t even know what GDP was last quarter yet! But while we wait for these crucial data, we float in a sea of information on all aspects of the economy: employment, production, sales, inventories, you name it. . . . Processing this information to figure out if it is rainy or sunny out there in the economy is the bread and butter of economists on trading desks, at central banks, and in the media. Thankfully, recent advances in computational and statistical methods have led to the development of automated real-time solutions to this challenging big data problem, with an approach commonly referred to as nowcasting. This post describes how we apply these techniques here at the New York Fed to produce the FRBNY Nowcast, and what we can learn from it. It also serves as an introduction to our Nowcasting Report, which we will update weekly on our website starting this Friday, April 15.

After navigating a few winding hallways at Uber HQ to find a tucked away conference room, I’m chatting with Andrew Chen about one of hi

On the night of the Iowa caucus, Dstillery flagged all the [ad network-mediated ad] auctions that took place on phones in latitudes and longitudes near caucus locations. It wound up spotting 16,000 devices on caucus night, as those people had granted location privileges to the apps or devices that served them ads. It captured those mobile ID’s and then looked up the characteristics associated with those IDs in order to make observations about the kind of people that went to Republican caucus locations (young parents) versus Democrat caucus locations. It drilled down further (e.g., ‘people who like NASCAR voted for Trump and Clinton’) by looking at which candidate won at a particular caucus location.