Knowledge Hut

APRIL 23, 2024

Data plays a crucial role in identifying opportunities for growth and decision-making in today's business landscape. Business intelligence collects techniques, tools, and methodologies organizations use to transform raw data into valuable information and meaningful insights. Wrapping Up! So, what is the future of BI?

Business Intelligence 52

Business Intelligence BI Data Analysis Media 52

Data Engineering Weekly

MAY 8, 2023

Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone. This data collection method was chosen because it was simple to deploy, with each employee responsible for their own receipts.

Process 52

Process Banking Raw Data Finance 52

Monte Carlo

MAY 28, 2024

Popular Data Ingestion Tools Choosing the right ingestion technology is key to a successful architecture. Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Snowflake

JUNE 30, 2023

To make that happen, it leverages the breadth of the Snowflake platform to transform raw data from multiple financial and operational systems into a common data model that users can understand more easily. semantha seeks to eliminate information overload with AI services for processing unstructured data like text and video.

Unstructured Data 94

Unstructured Data Raw Data Python SQL 94

Knowledge Hut

JANUARY 18, 2024

For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data. BI developers must use cloud-based platforms to design, prototype, and manage complex data.

Data Science 98

Data Science Business Analyst ETL Method Data Architect 98

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

DECEMBER 14, 2022

Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. However, with the advent of cloud-based infrastructure, ETL is changing towards ELT. Second, during transformations, data gets reshaped into some specific form.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Assess the needs and goals of the business.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. Google Cloud Platform and/or BigLake Google offers a couple options for building data lakes.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 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

Meltano

OCTOBER 5, 2022

What Is Data Engineering? Data engineering is the process of designing systems for collecting, storing, and analyzing large volumes of data. Put simply, it is the process of making raw data usable and accessible to data scientists, business analysts, and other team members who rely on data.

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 84

Engineering Raw Data Data Science Scala 84

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts. Let’s take a closer look.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. What do Data Engineers Do? This can be easier when you are using existing cloud services.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

APRIL 23, 2024

Sentiment Analysis and Natural Language Processing (NLP): AI and ML algorithms can process and analyze unstructured data, like text and speech, to better understand consumer sentiments. Large datasets are processed and stored using cost-effective methods, and organizations can extend their infrastructure as data quantities rise.

Big Data 52

Big Data Retail Recruitment Transportation 52

Monte Carlo

AUGUST 19, 2023

It becomes especially important to have a data storage and processing layer when you start to deal with large amounts of data and are holding that data for a long period of time and need it to be readily available for analysis.

Building 52

Building BI Data Lake Data Governance 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 98

AWS Scala Metadata Data Lake 98

Databand.ai

JULY 19, 2023

ELT is commonly used in big data projects and real-time processing where speed and scalability are critical. In the past, data was often stored in a single location, such as a database or a data warehouse. This dispersed data environment creates a challenge for businesses that need to access and analyze their data.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

APRIL 25, 2024

Variety: Unstructured data, semi-structured data, and raw data are only a few examples of the variety of data kinds that exist. Each day, the company's 96 million users generate enormous amounts of data. As an illustration, consider the music streaming service Spotify.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

SEPTEMBER 15, 2022

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. Ramsey International Modern Data Platform Architecture. What is a data mesh?

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Grouparoo

NOVEMBER 16, 2021

Loading is the process of warehousing the data in an accessible location. The advent of cloud-based solutions has enabled a switch to Extract, Load, and Transform (ELT). The difference here is that warehoused data is in its raw form, with the transformation only performed on-demand following information access.

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

Meltano

OCTOBER 5, 2022

This involves continually striving to reduce wasted effort, identify gaps and correct them, and improve data development and deployment processes. While definitions of each of these roles may vary across organizations, each is responsible for making data available to data analysts, scientists, and other team members who depend on it.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 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. It not only consumes more memory but also slackens data transfer.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Monte Carlo

JUNE 14, 2023

Data pipeline architecture typically consisted of hardcoded pipelines that cleaned, normalized, and transformed the data prior to loading into a database using an ETL pattern. With cost and physical compute/storage limitations largely lifted, data engineers started to optimize data pipeline architecture for speed and agility.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Towards Data Science

FEBRUARY 9, 2024

Fivetran still seems like the undeniable leader in the managed ETL category, but it has some stiff competition via up & comers like Airbyte and big cloud providers that have been strengthening their platform offerings.

Building 80

Building Transportation Data Lake Metadata 80

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. Integrate.io

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

AUGUST 11, 2021

Storage Layer: This is a centralized repository where all the data loaded into the data lake is stored. HDFS is a cost-effective solution for the storage layer since it supports storage and querying of both structured and unstructured data. Raw data is allowed to flow into a data lake, sometimes with no immediate use.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

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. Microsoft developed it and combines business analytics, data visualization, and best practices.

BI 98

BI Business Intelligence Machine Learning SQL 98

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

ProjectPro

JANUARY 27, 2023

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

JUNE 16, 2023

Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. These insights can be applied to drive company outcomes and make educated decisions.

Programming Language 52

Programming Language Cloud Computing Data Preparation Data Science 52