WHY IT MATTERS: Digital Transformation

Le référencement local est devenu de plus en plus important. En 2020, plus de 65% des recherches ont été effectuées avec des intentions de recherches locales, c’est à dire une pratique visant à positionner une entreprise sur une requête impliquant un critère géographique. 

In this article, we’ll present seven of the key best practices you should adhere to when designing, implementing and operationalizing your data lake. These are things that will mostly be automatically implemented if you’re using Upsolver, but if you’re building your data lake ‘manually’ you’ll need to ensure they’re done correctly if you want to get the most value out of your data lake architecture.
While we will mostly be referring to Amazon S3 as the storage layer, these best practices would also apply for a data lake built on a different cloud or using Hadoop on-premise.

Data lakes are key to scalable, open data architectures – but they can pose challenges to data engineering teams. Efficient data integration is the difference between a bunch of log files sitting in Amazon S3 or Azure Storage and a high-performance data lake that provides real value to analytics, data science and engineering teams.
In this guide we will cover some of the essential best practices and guidelines on how to make your data lake analytics-ready using cloud data processing and integration tools.

OpenAI is committed to the safe deployment of AI. Since the launch of our API, we’ve made deploying applications faster and more streamlined while adding new safety features. Our progress with safeguards makes it possible to remove the waitlist for GPT-3. Starting today, developers in supported countries can sign

We’ve fine-tuned GPT-3 to more accurately answer open-ended questions using a text-based web browser. Our prototype copies how humans research answers to questions online – it submits search queries, follows links, and scrolls up and down web pages. It is trained to cite its sources, which makes it easier to give feedback to improve factual accuracy. We’re excited about developing more truthful AI,1 but challenges remain, such as coping with unfamiliar types of questions.

Here’s a sample communication architecture for a remote-friendly company.

When the botnet loses communication to a C2 domain—typically because there is some sort of law enforcement action—the botnet knows to go and scan the entire public Bitcoin blockchain and it looks for transactions between those three Bitcoin addresses,” said Plante. In other words, every time a C2 domain gets taken down, Glupteba can automatically reconstitute via a new domain address sent through the gang’s crypto wallets.
The decentralized nature of the blockchain means that there isn’t really any way to block these messages from going through, or to incapacitate the associated crypto addresses, said Plante.

While CDP vendors may claim to do everything, the fact is they can’t.

We need to be able to fit new concepts and components neatly into existing architecture—to adapt to changes without disruption.

At first glance, the data fabric and the data mesh concepts sound quite similar. Meshes are often made from a type of fabric, after all, and they are both malleable items that can be lain atop things–in this case, your IT systems that are subject to the ever-growing data crush.

But there are fundamental differences to these two approaches, so it’s worth taking some time to learn their differences.

Gartner Top 10 Data and Analytics Trends for 2021

There are many tools available for doing large-scale data analysis, and picking the right one for a given job is critical. Here, we take an in-depth analysis of the architecture and performance characteristics of a completely serverless data processing platform. While the approach isn’t applicable for every use case, it has a very low total cost of ownership (TCO) and because AWS Lambda allows us to run arbitrary code easily, this approach provides the flexibility to handle non-standard data formats easily.

A majority of companies now adopt AI, and leaders are using more sophisticated tools and practices.

12 technology trends that will help shape the future of digital business.

There's been some interesting debate lately about CDPs vs. CDWs — customer data platforms vs. cloud data warehouses. If CDWs such as Snowflake, Databricks, AWS Redshift, etc., are becoming a universal data layer in companies, is there still a role for domain-specific data platforms, such as marketing-controlled CDPs? The short answer, in my opinion, is 'Yes, but it depends…' There is still a significant distinction between live business operations systems that run in real-time serving

Where should I run my stuff on Google Cloud? #GCPSketchnote

Put this all together and what do you get? If you are an optimist, the office of the future will be a spacious, collaborative environment that makes the commute worth it. If you are a pessimist, it will be a building full of heavily surveilled drunkards. In reality, pragmatic considerations—how much time is left on the lease, the physical constraints of a building’s layout, uncertainty about the path of the pandemic—will determine the pace of change. Whatever happens, the office won't be what it was.

Nonfungible tokens (NFTs), digital humans and physics-informed AI join the 25 technology profiles on the Gartner emerging technologies hype cycle for 2021.

Emerging Technology Roadmap benchmark adoption plan, risk factors, and value drivers. Use this roadmap to help you make technology investment decisions for the coming 12- to 24-month time period.

Performance chapter of the 2021 Web Almanac covering Core Web Vitals (Largest Contentful Paint, Cumulative Layout Shift, First Input Delay) as well as First Contentful Paint and Time to First Byte

The goal of the Web Almanac’s Structured Data chapter is to explore how structured data is currently being used across the web. We hope that this will provide insight into the landscape, the challenges, and the opportunities at hand.

Collect your thoughts and notes without leaving the command line.

Fluency on the command line is a skill often neglected or considered arcane, but it improves your flexibility and productivity as an engineer in both obvious and subtle ways. This is a selection of notes and tips on using the command-line that we've found useful when working on Linux. Some tips are elementary, and some are fairly specific, sophisticated, or obscure. This page is not long, but if you can use and recall all the items here, you know a lot.

Within a matter of hours of each day beginning, we ingest tens of billions of records from online sources to HDFS, aggregated across 50+ offline data flows, and visualize 40+ metrics across our business lines to support a dashboard providing company leaders with timely and critical business insights. Dubbed the Daily Executive Dashboard (DED), this dashboard contains critical growth, engagement, and bookings metrics that indicate the health of LinkedIn’s business. In this blog post, we’ll spotlight the challenges to DED’s delivery and performance posed by the growing complexity of computing and aggregating these metrics, and how this dashboard transformed our approach to data pipelines across the company.

This year's State of the API report covers the largest and most comprehensive survey on APIs, ever. More than 28,000 developers and API professionals shared their thoughts on a range of topics, including their organizations' development priorities, how they get their work done, and where they see the industry going. We combined this data with data we've observed on the Postman API Platform to build a robust picture of the current state—and the future—of APIs.