ProjectPro

DECEMBER 17, 2021

Data science and artificial intelligence might be the buzzwords of recent times, but they are of no value without the right data backing them. The process of data collection has increased exponentially over the last few years. NoSQL databases are designed to store unstructured data like graphs, documents, etc.,

Data Science 52

Data Science SQL NoSQL Programming Language 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

NOVEMBER 28, 2023

As a Data Engineer, you must: Work with the uninterrupted flow of data between your server and your application. Work closely with software engineers and data scientists. Relational database management systems (RDBMS) remain the key to data discovery and reporting, regardless of their location.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

ProjectPro

APRIL 17, 2015

This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. Businesses are targeting to invest in advanced methods of encryption to prevent big data breaches by adopting novelties in security technologies and training staff on security aspects.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

Rockset

OCTOBER 26, 2022

Also, DynamoDB, as a NoSQL database, doesn’t support SQL commands such as JOINING multiple tables. That’s where DynamoDB’s analytical limitations reared their ugly heads. For instance, to make any DynamoDB query run reasonably fast, we first needed to create a secondary index with a sort key tailored for that query.

SQL 52

SQL NoSQL Database Aggregated Data 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. It ensures that the data collected from cloud sources or local databases is complete and accurate.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Ascend.io

SEPTEMBER 14, 2023

Here are some examples of how Python can be applied to various facets of data engineering: Data Collection Web scraping has become an accessible task thanks to Python libraries like Beautiful Soup and Scrapy, empowering engineers to easily gather data from web pages.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Rockset

APRIL 12, 2021

With a mission to digitize every aspect of construction materials logistics, the company launched CONNEX in 2019 to provide a SaaS application where suppliers, transportation providers and contractors on jobsites can collaborate on all the data collected by Command Alkon’s systems.

NoSQL 40

NoSQL Transportation Electronics Data Preparation 40

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

JUNE 20, 2023

Additionally, they create and test the systems necessary to gather and process data for predictive modelling. Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

MARCH 27, 2024

MongoDB This free, open-source platform, which came into the limelight in 2010, is a document-oriented (NoSQL) database that is used to store a large amount of information in a structured manner. Although it's open source, it only supports 10000 data rows and one logical processor. Features: Various file types (SAS, ARFF, etc.)

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Grouparoo

OCTOBER 6, 2021

13 Column Names as Contracts Standardize columns names to minimize confusion 14 Consensual, Privacy-Aware Data Collection At some point does Grouparoo get properties noted as PII and what it means for a profile to opt out? 15 Cultivate Good Working Relationships with Data Consumers Practice empathy 16 Data Engineering !

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

JULY 3, 2023

Like IoT devices, sensors, social media platforms, financial data, etc. Data Storage: Real-Time data ingestion infrastructure requires storage capable of handling and storing high amounts of data with low latency. It supports high-speed data streams from various sources and provides real-time insights.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Rockset

OCTOBER 20, 2021

You would create a Rockset collection for each data stream, and then set up SQL-Based Rollups to perform transformations and aggregations on the data as it is written into Rockset. This can be helpful when you want to reduce the size of large scale data streams, deduplicate data, or partition your data.

SQL 52

SQL PostgreSQL MongoDB NoSQL 52

Knowledge Hut

JANUARY 22, 2024

Data Engineering These courses provide expertise on building and maintaining data pipelines for AI/ML applications. Key topics include data collection, storage formats like databases, data warehouses, data lakes, transforming and processing data using ETL, batch and stream processing.

Data Science 52

Data Science Certification Education Data Lake 52

Knowledge Hut

APRIL 24, 2024

cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, threshold(gray_image, 127, 255, cv2.THRESH_BINARY) THRESH_BINARY) contours, _ = cv2.findContours(thresh, findContours(thresh, cv2.RETR_TREE, RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) CHAIN_APPROX_SIMPLE) max_area = 0 max_cnt = None for cnt in contours: area = cv2.contourArea(cnt)

Software Engineer 52

Software Engineer Software Engineering Coding Project 52

AltexSoft

FEBRUARY 11, 2023

Hands-on experience with a wide range of data-related technologies The daily tasks and duties of a data architect include close coordination with data engineers and data scientists. They also must understand the main principles of how these services are implemented in data collection, storage and data visualization.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

DECEMBER 26, 2023

Some of these ideas consist of: Big data technology and technologists deal with a number of similar problems, such as data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns. Relational and non-relational databases, such as RDBMS, NoSQL, and NewSQL databases.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Knowledge Hut

OCTOBER 27, 2023

cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, threshold(gray_image, 127, 255, cv2.THRESH_BINARY) THRESH_BINARY) contours, _ = cv2.findContours(thresh, findContours(thresh, cv2.RETR_TREE, RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) boundingRect(max_cnt) else: return None image = cv2.imread("fingerprint.jpg")

Software Engineer 98

Software Engineer Software Engineering Coding Project 98

Knowledge Hut

OCTOBER 24, 2023

SQL and SQL Server BAs must deal with the organization's structured data. They ought to be familiar with databases like Oracle DB, NoSQL, Microsoft SQL, and MySQL. BAs can store and process massive volumes of data with the use of these databases. Understanding company procedures will help you attain success.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

ProjectPro

APRIL 19, 2021

Here’s a quick breakdown of other day-to-day data analyst responsibilities apart from meetings and reporting– Collect data from diverse sources and maintain them. Build and deploy data collection systems. Define novel data collection strategies as per business needs.

Portfolio 40

Portfolio Data Finance Certification 40

ProjectPro

JULY 3, 2015

. “SAP systems hold vast amounts of valuable business data -- and there is a need to enrich this, bring context to it, using the kinds of data that is being stored in Hadoop. SAP has announced a deeper embrace of the big data platform Hadoop. SAP and Hadoop need not work on the same system to render customer value.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

ProjectPro

JUNE 2, 2015

It is difficult to make sense out of billions of unstructured data points (in the form of news articles, forum comments, and social media data) without powerful technologies like Hadoop, Spark and NoSQL in place. times better than those with ad-hoc or decentralized teams.

Big Data 40

Big Data Hadoop Banking Retail 40

Cloudera

AUGUST 30, 2022

A data mesh supports distributed, domain-specific data consumers and views data as a product, with each domain handling its own data pipelines. Towards Data Science ). Solutions that support MDAs are purpose-built for data collection, processing, and sharing. Forrester ).

Data Architecture 77

Data Architecture Architecture Data Lake NoSQL 77

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. How small file problems in streaming can be resolved using a NoSQL database. Using Flume to handle small files in streaming.

Hadoop 40

Hadoop Big Data Coding Project 40

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

SEPTEMBER 21, 2023

In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. Fluentd is a data collector and a lighter-weight alternative to Logstash. What is Elasticsearch?

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

MAY 14, 2021

Big Data analytics processes and tools. Data ingestion. The process of identifying the sources and then getting Big Data varies from company to company. It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

U-Next

AUGUST 17, 2022

Because of this, all businesses—from global leaders like Apple to sole proprietorships—need Data Engineers proficient in SQL. NoSQL – This alternative kind of data storage and processing is gaining popularity. The term “NoSQL” refers to technology that is not dependent on SQL, to put it simply.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

ProjectPro

MAY 23, 2015

Walmart acquired a small startup Inkiru based in Palo Alto, California to boost its big data capabilites.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

AltexSoft

JULY 27, 2021

Google singles out four key phases through which a recommender system processes data. They are information collection, storing, analysis, and filtering. Data collection. The initial phase involves gathering relevant data to create a user profile or model for prediction tasks. Let’s have a closer look at each phase.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

AltexSoft

JUNE 7, 2021

The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. The framework provides a way to divide a huge data collection into smaller chunks and shove them across interconnected computers or nodes that make up a Hadoop cluster. Data storage options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

AUGUST 21, 2015

Data can either be ingested through batch jobs that run every 15 minutes, once every night and so on or through streaming in real-time from 100 ms to 120 seconds. ii) Data Storage – The subsequent step after ingesting data is to store it either in HDFS or NoSQL database like HBase. If yes, then explain how.

Hadoop 40

Hadoop Big Data Metadata Unstructured Data 40

AltexSoft

NOVEMBER 23, 2021

The responsibility of this layer is to access the information scattered across multiple source systems, containing both structured and unstructured data , with the help of connectors and communication protocols. Data virtualization platforms can link to different data sources including.

Process 69

Process Data Lake Metadata Data Warehouse 69