Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. They also need knowledge of Data Warehousing, Analytics, and Business Intelligence concepts, Data Visualization, etc.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

JANUARY 18, 2024

Data Science is a field of study that handles large volumes of data using technological and modern techniques. This field uses several scientific procedures to understand structured, semi-structured, and unstructured data. Both data science and software engineering rely largely on programming skills.

Software Engineer 97

Software Engineer Software Engineering Data Science Engineering 97

Knowledge Hut

DECEMBER 29, 2023

Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 22, 2023

Power BI is a technology-driven business intelligence tool or an array of software services, apps, and connectors to convert unrelated and raw data into visually immersive, coherent, actionable, and interactive insights and information. Power Map Power map is a 3-D data visualization tool. What is Power BI?

BI 98

BI Business Intelligence Machine Learning SQL 98

Knowledge Hut

JUNE 20, 2023

They transform unstructured data into scalable models for data science. Data Engineer vs Machine Learning Engineer: Responsibilities Data Engineer Responsibilities: Analyze and organize unstructured data Create data systems and pipelines. Assess the needs and goals of the business.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

APRIL 20, 2021

Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. What is Streaming Analytics?

Hospitality 93

Hospitality Kafka Retail Data Ingestion 93

Snowflake

APRIL 5, 2023

With Snowflake’s support for multiple data models such as dimensional data modeling and Data Vault, as well as support for a variety of data types including semi-structured and unstructured data, organizations can accommodate a variety of sources to support their different business use cases.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

U-Next

AUGUST 18, 2022

Data Scientist is a highly dynamic job and requires a person to be well-versed in AI, business intelligence, Machine Learning earning, etc. What Does a Data Scientist Do? You could receive ten different responses if you consult ten distinct Data Scientists with the same question. Learn more about it here.

Unstructured Data 40

Unstructured Data Medical Data Science Business Intelligence 40

Knowledge Hut

DECEMBER 27, 2023

A business generates data daily related to production, sales, marketing , customer feedback, team structure, costs, and other metrics. Sometimes it isn't easy to get a clear picture of the business because of unstructured data, and data visualization benefits the company by visually structuring the data.

Telecommunication 52

Telecommunication Bytes Machine Learning Insurance 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

JANUARY 30, 2024

Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. Unstructured Data: Unstructured data, like free-form text, can be challenging to work with but holds valuable insights.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

JULY 4, 2023

Roles and Responsibilities of Data Engineer Analyze and organize raw data. Build data systems and pipelines. Evaluate business needs and objectives. Conduct complex data analysis and report on results. Prepare data for prescriptive and predictive modeling. Interpret trends and patterns.

Data Analytics 52

Data Analytics Data Architect Transportation Data Science 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. In addition to this, they make sure that the data is always readily accessible to consumers.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

U-Next

AUGUST 11, 2022

Deep Learning is an AI Function that involves imitating the human brain in processing data and creating patterns for decision-making. It’s a subset of ML which is capable of learning from unstructured data. Why Should You Pursue A Career In Artificial Intelligence? There are excellent career opportunities in AI.

Medical 52

Medical Computer Science Scala Machine Learning 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. "The Art of Data Science" Roger D.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

JULY 26, 2023

They enable organizations to use data as an asset, resulting in greater operational efficiency, improved decision-making, and an edge over competitors in today's data-driven corporate world. Database applications also help in data-driven decision-making by providing data analysis and reporting tools.

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

APRIL 20, 2023

To combat these dirty challenges thrown by hackers, the field of data science has emerged as a powerful player in the battleground against cybercrimes. Once this knowledge is applied, the data is cleaned and organized using techniques such as data analysis, feature engineering, and machine learning to make it usable and reliable.

Data Science 52

Data Science Computer Science Healthcare Recruitment 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 2- Internal Data transformation at LakeHouse.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Databand.ai

DECEMBER 13, 2022

Currently, as the Associate Director of Platform and DevOps Engineering at MIT, he is focused on marrying the worlds of software engineering, systems automation, and data analysis. Bill was also named by ComputerWorld as one of the ten most influential people in the history of the computer profession.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

DECEMBER 26, 2023

Let us first get a clear understanding of why Data Science is important. What is the need for Data Science? If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

SEPTEMBER 11, 2015

For professionals from BI background, learning Hadoop is necessary because with data explosion it is becoming difficult for traditional databases to store unstructured data. Hadoop still has a long way to go when it comes to presenting clean and readable data solutions.

Hadoop 52

Hadoop Java BI Big Data 52

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. Our customers have sales people and use software, but they cannot step into the traditional way of buying business intelligence.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Knowledge Hut

MARCH 27, 2024

You can check out the Big Data Certification Online to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. To get your business in the direction you want, you need to choose the right tools for big data analysis based on your business goals, needs, and variety.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

DECEMBER 22, 2023

Statistics are used by data scientists to collect, assess, analyze, and derive conclusions from data, as well as to apply quantifiable mathematical models to relevant variables. Microsoft Excel An effective Excel spreadsheet will arrange unstructured data into a legible format, making it simpler to glean insights that can be used.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

ProjectPro

JUNE 9, 2021

Wikipedia defines data science as an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains. Who is a Data Scientist?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

JANUARY 16, 2024

Data lake and data warehouse convergence The data lake vs data warehouse question is constantly evolving. The maxim that data warehouses hold structured data while data lakes hold unstructured data is quickly breaking down.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Edureka

AUGUST 2, 2023

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used. What does a Data Processing Analysts do ?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Edureka

FEBRUARY 9, 2023

This includes practical knowledge of data ingestion methods like incremental loading and bulk loading, as well as experience with data transformation using Azure Data Factory. It’s a versatile language that is well-suited to a wide range of data engineering tasks, and its use in Azure is widespread.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

AUGUST 25, 2023

Data warehouses are often the most sensible choice for data platforms whose primary use case is for data analysis and reporting. With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JULY 24, 2023

Companies of all sizes and across various sectors utilize SQL for data analysis and reporting as the volume of data generated daily increases. SQL helps businesses to query and extract data from big datasets, offering insights into market trends, customer behavior, and other crucial elements that drive decision-making.

SQL 52

SQL Database Process NoSQL 52

ProjectPro

JANUARY 27, 2023

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

BI 52

BI ETL Tools Retail Healthcare 52