Alec  Nikolaus

Alec Nikolaus

1596036600

Edge Is Taking Data to a Higher Level

This article is an introduction to edge computing. Let’s have a look at what edge computing is and the advantages.

Introduction

Over the years of computing, the processing and storage of data systems that are used in the interconnected computers have been based on the technology of cloud computing. Cloud computing has been based on the centralized data storage systems where all the devices performing some internet operations depend on the efficiency of the cloud service provider.

Since the data has often been centralized, various concerns including the security and the speed in operation have been raised regarding this setup of infrastructure. Since the data is centralized, a single breach can sabotage a large number of users. Moreover, people’s right to privacy may be violated since the service providers have an opportunity to access and monitor people’s details and demographic characteristics.

Latency to the information required may be experienced when the data is being transmitted from the cloud to the end-user due to factors such as the traffic and the distance.

The introduction of edge computing has proved to be effective in the problems associated with cloud computing. Let’s have a look at what edge computing is and the advantages.

Edge Computing From a Broad Perspective

The introduction of edge computing has led to the successful proximity of internet data to the end-user. This is done by installing the edge devices close to the end-user by different service providers. A system of interconnected nodes enables the transfer of data from one edge device to the other, hence resulting in the ease of accessing information.

The response time which has been a critical concern especially to the heavy commercial consumers has been solved by this great technology of edge computing. Since the edge devices are close to the end-user, the time of travel of the information from one end-user to the other or from an end-user to a system of AI in the edge devices is minimized. Besides, the traffic that exists in cloud computing is eliminated since the decentralized edge devices serve few users, consequently, the efficiency in the response time and rate.

What Is So Unique in Edge Computing

The system of a computer program that functions to avail data to users at their location and delivers it, can be referred to as an edge device.

Most service providers such as the CCTV cameras, traffic systems in roundabouts and other critical points that heavily depend on the real-time processing of data find the edge computing useful in these functions. The CCTV cameras collect a huge amount of data that can be as high as 10 GB per second especially in a moving car for about a mile. For the data to be transferred to the cloud for the AI (artificial intelligence) to assist in its processing, there can be latency experienced in the process resulting in poor decision making especially in the self-driving cars or the AI dependent systems.

Edge devices enable the real-time processing of the data in huge volumes and at the shortest distance hence the elimination of the latency experienced when cloud computing is adopted. Cloud computing might be efficient in the operation of huge data for its capacity and the extent of specialized and sophisticated hardware installed in it, the edge devices are unchallenged in the operation of real-time data.

#cloud computing #data #edge computing #edge #interner of things #cloud

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Edge Is Taking Data to a Higher Level
Siphiwe  Nair

Siphiwe Nair

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Cyrus  Kreiger

Cyrus Kreiger

1617959340

4 Tips To Become A Successful Entry-Level Data Analyst

Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand. Even as we transition to more automated data collection systems, data analysts remain a crucial piece in the data puzzle. Not only do they build the systems that extract and organize data, but they also make sense of it –– identifying patterns, trends, and formulating actionable insights.

If you think that an entry-level data analyst role might be right for you, you might be wondering what to focus on in the first 90 days on the job. What skills should you have going in and what should you focus on developing in order to advance in this career path?

Let’s take a look at the most important things you need to know.

#data #data-analytics #data-science #data-analysis #big-data-analytics #data-privacy #data-structures #good-company

Pesquisa Linear em Python

Nesta postagem python, você aprenderá o seguinte:

  • O que é uma pesquisa linear?
  • Algoritmo de pesquisa linear
  • Escreva um programa Python para pesquisa linear usando loop while
  • Escreva um programa Python para pesquisa linear usando o loop for
  • Pesquisa linear no programa Python usando recursão

O que é uma pesquisa linear?

Em primeiro lugar, uma pesquisa linear, também conhecida como pesquisa sequencial, este método é usado para localizar um elemento dentro de uma lista ou array. Ele verifica cada elemento da lista um por um / sequencialmente até que uma correspondência seja encontrada ou toda a lista tenha sido pesquisada.

Algoritmo de pesquisa linear

Implemente a pesquisa linear seguindo as etapas abaixo:

  • Percorra a lista / array usando um loop.
  • Em cada iteração, associe o target valor ao  valor fornecido da lista / matriz.
    • Se os valores corresponderem, retorne o índice atual da lista / matriz.
    • Caso contrário, vá para o próximo elemento de array / lista.
  • Se nenhuma correspondência for encontrada, retorne  -1.

Escreva um programa Python para pesquisa linear usando loop while

# python program for linear search using while loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

i = 0
flag = False

while i < len(lst):
	if lst[i] == x:
		flag = True
		break

	i = i + 1

if flag == 1:
	print('{} was found at index {}.'.format(x, i))
else:
	print('{} was not found.'.format(x))

Depois de executar o programa, a saída será:

Enter size of list :-  5
Enter the array of 0 element :-  10
Enter the array of 1 element :-  23
Enter the array of 2 element :-  56
Enter the array of 3 element :-  89
Enter the array of 4 element :-  200
Enter number to search in list :-  89
89 was found at index 3.

Escreva um programa Python para pesquisa linear usando o loop for

# python program for linear search using for loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

i = 0
flag = False

for i in range(len(lst)):
    if lst[i] == x:
        flag = True
        break

if flag == 1:
	print('{} was found at index {}.'.format(x, i))
else:
	print('{} was not found.'.format(x))

Depois de executar o programa, a saída será:

Enter size of list :-  6
Enter the array of 0 element :-  25
Enter the array of 1 element :-  50
Enter the array of 2 element :-  100
Enter the array of 3 element :-  200
Enter the array of 4 element :-  250
Enter the array of 5 element :-  650
Enter number to search in list :-  200
200 was found at index 3.

Pesquisa linear no programa Python usando recursão

# python program for linear search using for loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

# Recursive function to linear search x in arr[l..r]  
def recLinearSearch( arr, l, r, x): 
    if r < l: 
        return -1
    if arr[l] == x: 
        return l 
    if arr[r] == x: 
        return r 
    return recLinearSearch(arr, l+1, r-1, x) 

res = recLinearSearch(lst, 0, len(lst)-1, x) 

if res != -1:
	print('{} was found at index {}.'.format(x, res))
else:
	print('{} was not found.'.format(x))

Depois de executar o programa, a saída será:

Enter size of list :-  5
Enter the array of 0 element :-  14
Enter the array of 1 element :-  25
Enter the array of 2 element :-  63
Enter the array of 3 element :-  42
Enter the array of 4 element :-  78
Enter number to search in list :-  78
78 was found at index 4.

Линейный поиск в Python

В этом посте на Python вы узнаете следующее:

  • Что такое линейный поиск?
  • Алгоритм линейного поиска
  • Напишите программу на Python для линейного поиска с использованием цикла while
  • Напишите программу на Python для линейного поиска с использованием цикла For
  • Линейный поиск в программе Python с использованием рекурсии

Что такое линейный поиск?

Прежде всего, линейный поиск, также известный как последовательный поиск, этот метод используется для поиска элемента в списке или массиве. Он проверяет каждый элемент списка один за другим / последовательно, пока не будет найдено совпадение или пока не будет выполнен поиск по всему списку.

Алгоритм линейного поиска

Реализуйте линейный поиск, выполнив следующие шаги:

  • Просмотрите список / массив, используя цикл.
  • На каждой итерации связывайте  target значение с заданным значением списка / массива.
    • Если значения совпадают, вернуть текущий индекс списка / массива.
    • В противном случае перейдите к следующему элементу массива / списка.
  • Если совпадений не найдено, вернитесь  -1.

Напишите программу на Python для линейного поиска с использованием цикла while

# python program for linear search using while loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

i = 0
flag = False

while i < len(lst):
	if lst[i] == x:
		flag = True
		break

	i = i + 1

if flag == 1:
	print('{} was found at index {}.'.format(x, i))
else:
	print('{} was not found.'.format(x))

После выполнения программы вывод будет:

Enter size of list :-  5
Enter the array of 0 element :-  10
Enter the array of 1 element :-  23
Enter the array of 2 element :-  56
Enter the array of 3 element :-  89
Enter the array of 4 element :-  200
Enter number to search in list :-  89
89 was found at index 3.

Напишите программу на Python для линейного поиска с использованием цикла For

# python program for linear search using for loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

i = 0
flag = False

for i in range(len(lst)):
    if lst[i] == x:
        flag = True
        break

if flag == 1:
	print('{} was found at index {}.'.format(x, i))
else:
	print('{} was not found.'.format(x))

После выполнения программы вывод будет:

Enter size of list :-  6
Enter the array of 0 element :-  25
Enter the array of 1 element :-  50
Enter the array of 2 element :-  100
Enter the array of 3 element :-  200
Enter the array of 4 element :-  250
Enter the array of 5 element :-  650
Enter number to search in list :-  200
200 was found at index 3.

Линейный поиск в программе Python с использованием рекурсии

# python program for linear search using for loop

#define list
lst = []

#take input list size
num = int(input("Enter size of list :- "))

for n in range(num):
    #append element in list/array
    numbers = int(input("Enter the array of %d element :- " %n))
    lst.append(numbers)

#take input number to be find in list   
x = int(input("Enter number to search in list :- "))

# Recursive function to linear search x in arr[l..r]  
def recLinearSearch( arr, l, r, x): 
    if r < l: 
        return -1
    if arr[l] == x: 
        return l 
    if arr[r] == x: 
        return r 
    return recLinearSearch(arr, l+1, r-1, x) 

res = recLinearSearch(lst, 0, len(lst)-1, x) 

if res != -1:
	print('{} was found at index {}.'.format(x, res))
else:
	print('{} was not found.'.format(x))

После выполнения программы вывод будет:

Enter size of list :-  5
Enter the array of 0 element :-  14
Enter the array of 1 element :-  25
Enter the array of 2 element :-  63
Enter the array of 3 element :-  42
Enter the array of 4 element :-  78
Enter number to search in list :-  78
78 was found at index 4.