Pickl AI

OCTOBER 15, 2024

Summary: Selecting the right ETL platform is vital for efficient data integration. Consider your business needs, compare features, and evaluate costs to enhance data accuracy and operational efficiency. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes.

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Data Science Blog

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?

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The MLOps Blog

MAY 17, 2023

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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Towards AI

JANUARY 28, 2024

To start, get to know some key terms from the demo: Snowflake: The centralized source of truth for our initial data Magic ETL: Domo’s tool for combining and preparing data tables ERP: A supplemental data source from Salesforce Geographic: A supplemental data source (i.e., Instagram) used in the demo Why Snowflake?

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Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Smart Data Collective

APRIL 29, 2020

Data management approaches are varied and may be categorised in the following: Cloud data management. The storage and processing of data through a cloud-based system of applications. Master data management. Extraction, Transform, Load (ETL). Data transformation. Reference data management.

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Data Warehouse SQL Azure ETL 98

phData

NOVEMBER 9, 2023

Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. As a fundamental piece of the modern data stack , Snowflake is helping thousands of businesses store, transform, and derive insights from their data easier, faster, and more efficiently than ever before.

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phData

FEBRUARY 21, 2025

A data warehouse acts as a single source of truth for an organization’s data, providing a unified view of its operations and enabling data-driven decision-making. A data warehouse enables advanced analytics, reporting, and business intelligence. On the other hand, cloud data warehouses can scale seamlessly.

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phData

AUGUST 9, 2023

In short, ELT exemplifies the data strategy required in the era of big data, cloud, and agile analytics. With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse.

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How to Learn Machine Learning

APRIL 26, 2025

Data Cleaning and Preparation The tasks of cleaning and preparing the data take place before the analysis. This includes duplicate removal, missing value treatment, variable transformation, and normalization of data. So, they very often work with data engineers, analysts, and business partners to achieve that.

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Dataversity

MARCH 17, 2021

I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]. appeared first on DATAVERSITY.

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Analytics Analytics Data Lakes Data Warehouse 52

phData

MARCH 8, 2023

Fivetran is an automated data integration platform that offers a convenient solution for businesses to consolidate and sync data from disparate data sources. With over 160 data connectors available, Fivetran makes it easy to move data out of, into, and across any cloud data platform in the market.

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Data Warehouse Data Engineering Data Engineering Data Engineering 96

phData

OCTOBER 9, 2023

As organizations embrace the benefits of data vault, it becomes crucial to ensure optimal performance in the underlying data platform. One such platform that has revolutionized cloud data warehousing is the Snowflake Data Cloud. However, joining tables using a hash key can take longer than a sequential key.

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Data Science Blog

JUNE 27, 2023

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

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phData

SEPTEMBER 2, 2024

In this blog, we will cover the best practices for developing jobs in Matillion, an ETL/ELT tool built specifically for cloud database platforms. It can connect to multiple data warehouses, including the Snowflake AI Data Cloud , Delta Lake on Databricks, Amazon Redshift, Google BigQuery, and Azure Synapse Analytics.

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Precisely

APRIL 3, 2023

The Long Road from Batch to Real-Time Traditional “extract, transform, load” (ETL) systems were built under certain constraints, stemming from the cost of technology and implementation resources, as well as the inherent limits of computational power. Nevertheless, the result was always yesterday’s news.

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Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Big data analytics from 2022 show a dramatic surge in information consumption.

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Big Data Big Data Data Engineering Data Engineering 119

Alation

JANUARY 17, 2023

Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? A Note on the Shift from ETL to ELT.

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phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

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phData

JUNE 6, 2024

Data gets ingested, centralized, and deployed within your cloud data warehouse. This allows companies to use their pre-existing data tools and prevents the need for costly setups. Companies need to bring in data from a wide variety of sources to get a holistic view of the customer.

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Data Warehouse Cloud Data ETL Data Modeling 52

phData

APRIL 29, 2024

In our previous blog, Top 5 Fivetran Connectors for Financial Services , we explored Fivetran’s capabilities that address the data integration needs of the finance industry. Now, let’s cover the healthcare industry, which also has a surging demand for data and analytics, along with the underlying processes to make it happen.

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SQL Data Warehouse Azure Cloud Data 52

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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Data Science Machine Learning Machine Learning Data Visualization 150

phData

OCTOBER 17, 2023

The story is all too common – a business user requests some data, the data team creates/prioritizes a ticket, and said ticket is completed after some number of months (or weeks if you’re lucky) – just to have the data be wrong, and the whole process starts again. Those are scary for data teams to change.

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phData

SEPTEMBER 4, 2024

This article was co-written by Lynda Chao & Tess Newkold With the growing interest in AI-powered analytics, ThoughtSpot stands out as a leader among legacy BI solutions known for its self-service search-driven analytics capabilities. Suppose your business requires more robust capabilities across your technology stack.

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Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. At the same time, there is a stronger push for real-time analytics and real-time customer access to data.

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IBM Journey to AI blog

JULY 17, 2023

Visual modeling: Delivers easy-to-use workflows for data scientists to build data preparation and predictive machine learning pipelines that include text analytics, visualizations and a variety of modeling methods. ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks.

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Alation

OCTOBER 27, 2022

This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. To answer this question, I sat down with members of the Alation Data & Analytics team, Bindu, Adrian, and Idris. Let’s dive in. What do you do at Alation?

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phData

FEBRUARY 7, 2024

The Snowflake Data Cloud is a leading cloud data platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is called Snowpark, which provides an intuitive library for querying and processing data at scale in Snowflake.

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phData

FEBRUARY 14, 2023

Fivetran is the answer for anyone looking to focus their efforts on analytics and not pipeline management. This can provide the efficiency needed to spend more time developing analytic solutions instead of moving data. Replication of calculated values is not supported during Change Processing.

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Data Warehouse Azure AWS Database 59

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. Simply put, IDF standardizes data engineering processes. IDF works natively on cloud platforms like AWS.

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DataOps Data Pipeline Data Engineering Data Engineer 52

phData

APRIL 20, 2023

Data vault modeling is a hybrid approach that combines traditional relational data warehouse models with newer big data architectures to build a data warehouse for enterprise-scale analytics. Data loading is faster since multiple tables may be loaded concurrently due to hashing strategy.

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phData

JANUARY 4, 2023

Snowflake works with an entire ecosystem of tools including Extract Transform and Load (ETL), data integration, and analysis tools. Disaster Recovery Snowflake allows for an easy and automatic backup of data and enables faster disaster recovery of critical IT systems. This makes the task exceedingly difficult.

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phData

JULY 18, 2023

The good news is that there’s a concept called the Modern Data Stack that when utilized properly, consistently helps empower organizations to harness the full potential of their data. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

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phData

JULY 10, 2024

It is important in business to be able to manage and analyze data well. Sigma Computing , a cloud-based analytics platform, helps data analysts and business professionals maximize their data with collaborative and scalable analytics. These tools allow users to handle more advanced data tasks and analyses.

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SQL Data Warehouse Analytics Analytics 52

Alation

OCTOBER 19, 2021

The surge in data collection has only compounded this problem. New applications that don’t integrate with your tech or analytics stack will generate silos. If a junior employee has the best idea, data culture ensures that idea gets a shot. New Applications. If left unchecked, these will grow with time.

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Data Silos ETL Data Governance Cloud Data 52

phData

NOVEMBER 28, 2023

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready. Why Does it Matter? Contact phData today!

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Dataversity

SEPTEMBER 6, 2021

The rush to become data-driven is more heated, important, and pronounced than it has ever been. Businesses understand that if they continue to lead by guesswork and gut feeling, they’ll fall behind organizations that have come to recognize and utilize the power and potential of data. Click to learn more about author Mike Potter.

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