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The connected vehicle is reshaping our view of mobility and transportation. The goal is how rapidly companies can get the information to fleet managers, deploy predictive analytics and machine learning to report fast, and prevent or save the costs of the downtime. The industry is fast changing from the regular telematics used for data collection to a single gateway to provide connectivity to all the peripherals of the vehicle.
Read more: https://analyticsindiamag.com/what-is-the-role-of-analytics-in-connected-vehicles/
#analytics #machine-learning #datacollection
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In our previous posts in this series, we spoke at length about using PgBouncer and Pgpool-II , the connection pool architecture and pros and cons of leveraging one for your PostgreSQL deployment. In our final post, we will put them head-to-head in a detailed feature comparison and compare the results of PgBouncer vs. Pgpool-II performance for your PostgreSQL hosting !
The bottom line – Pgpool-II is a great tool if you need load-balancing and high availability. Connection pooling is almost a bonus you get alongside. PgBouncer does only one thing, but does it really well. If the objective is to limit the number of connections and reduce resource consumption, PgBouncer wins hands down.
It is also perfectly fine to use both PgBouncer and Pgpool-II in a chain – you can have a PgBouncer to provide connection pooling, which talks to a Pgpool-II instance that provides high availability and load balancing. This gives you the best of both worlds!
PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II
While PgBouncer may seem to be the better option in theory, theory can often be misleading. So, we pitted the two connection poolers head-to-head, using the standard pgbench tool, to see which one provides better transactions per second throughput through a benchmark test. For good measure, we ran the same tests without a connection pooler too.
All of the PostgreSQL benchmark tests were run under the following conditions:
We ran each iteration for 5 minutes to ensure any noise averaged out. Here is how the middleware was installed:
Here are the transactions per second (TPS) results for each scenario across a range of number of clients:
#database #developer #performance #postgresql #connection control #connection pooler #connection pooler performance #connection queue #high availability #load balancing #number of connections #performance testing #pgbench #pgbouncer #pgbouncer and pgpool-ii #pgbouncer vs pgpool #pgpool-ii #pooling modes #postgresql connection pooling #postgresql limits #resource consumption #throughput benchmark #transactions per second #without pooling
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Agrochemical companies manufacture a range of offerings for yield maximisation, pest resistance, hardiness, water quality and availability and other challenges facing farmers. These companies need to measure the efficacy of their products in real-world conditions, not just controlled experimental environments. Single-crop farms are divided into plots and a specific intervention performed in each. For example, hybrid seeds are sown in one plot while another is treated with fertilisers, and so on. The relative performance of each treatment is assessed by tracking the plants’ health in the plot where that treatment was administered.
#featured #deep learning solution #tiger analytics #tiger analytics deep learning #tiger analytics deep learning solution #tiger analytics machine learning #tiger analytics ml #tiger analytics ml-powered digital twin
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The overnight transformation of companies adopting new technologies and transitioning to a digital work environment amid pandemic has made upskilling the most critical component in a worker’s repertoire in 2021. While information, data and the ability to make the right decisions serve as a stabiliser across verticals, analytics and data science have become indispensable tools to navigate today’s career scene.
According to a recent Forrester study, the top two challenges decision-makers cited are — the lack of employees with data skillsets and the lack of skills among business users who must use data insights. Almost 66% of organisations believe there is a requirement for data literacy among employees, where 59% demand analytic efficiency. However, with a converged approach to analytics through democratising access to data, automating tedious and complex processes, and promoting upskilling of data and knowledge workers, organisations can create a thriving data and analytics culture within.
#featured #advancing data and analytics #alteryx adapt #alteryx advancing data and analytics #alteryx upskilling programs #analytics upskilling #data and analytics #data science and analytics #start your analytics journey with adapt
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More and more mobile applications are utilizing power WebView to customize the user experience on runtime. And it is all the more important to track users’ activities on the WebView.
However, Firebase analytics’s SDK doesn’t support sending events from WebView pages of the mobile app. So to use Analytics in WebView, its events must be forwarded to native code before they can be sent to analytics.
So,
First, we have to pass the events from WebView to native code.
Second, fetch the passed events in the native environment and send it to Firebase Analytics.
#google-analytics #web-analytics #analytics #firebase #digital-analytics
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The proliferation of big data analytics solutions has significantly redefined businesses’ data processing over the years. It has already proven a key solution for identifying and deriving meaningful insights from vast datasets. With emerging technologies like artificial intelligence, machine learning and the cloud, data professionals are now leveraging cognitive analytics to drive real-time decision making. It presents much greater potential than big data analytics, unlocking the value of big data by making a system more self-reliant, and information contained more accessible.
Since data is considered the oil of today’s digital economy, data analytics is an indispensable economic driver. Over the years, it has evolved exponentially including from descriptive to diagnostic and predictive to prescriptive. Cognitive analytics is now likely to become the next frontier of this data analytics trend. It exploits high-performance computing power by integrating artificial intelligence and machine learning techniques with data analytics approaches.
#big data #latest news #how can cognitive analytics go beyond big data analytics? #analytics #cognitive analytics #cognitive computing