Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Tableau

MAY 11, 2022

Certified data sources carefully chosen by site administrators and project leaders. Recommended data sources personally certified and/or automatically selected based on organizational usage patterns. Recommended database tables that are used frequently in data sources and workbooks published to your Tableau server.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Tableau

MAY 11, 2022

Certified data sources carefully chosen by site administrators and project leaders. Recommended data sources personally certified and/or automatically selected based on organizational usage patterns. Recommended database tables that are used frequently in data sources and workbooks published to your Tableau server.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

AWS Machine Learning Blog

FEBRUARY 14, 2024

In this post, we discuss how to use the comprehensive capabilities of Amazon Bedrock to perform complex business tasks and improve the customer experience by providing personalization using the data stored in a database like Amazon Redshift. Now you’re ready to connect to the EC2 instance using SSH. Open an SSH client.

AWS 140

AWS AI AI Database 140

AWS Machine Learning Blog

JUNE 12, 2025

Their goal for a beta product is to create a conversational AI assistant powered by large language models (LLMs) that allows VideoAmp’s data analysts and non-technical users such as content researchers and publishers to perform data analytics using natural language queries. The solution is connected to a data warehouse.

Analytics 86

Analytics Analytics SQL Data Warehouse 86

Dataconomy

MAY 26, 2025

Data cleansing and integration: Ensuring data quality through processes that contribute to a centralized data repository (data warehouse or data mart). Iterative analysis: Conducting initial analyses on smaller datasets and refining questions based on findings.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

Pickl AI

JULY 14, 2024

It highlights their unique functionalities and applications, emphasising their roles in maintaining data integrity and facilitating efficient data retrieval in database design and management. Understanding the significance of different types of keys in DBMS is crucial for effective database design and management.

Database 52

Database SQL Data Warehouse Data Analyst 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Dataconomy

SEPTEMBER 27, 2023

The Microsoft Certified Solutions Associate and Microsoft Certified Solutions Expert certifications cover a wide range of topics related to Microsoft’s technology suite, including Windows operating systems, Azure cloud computing, Office productivity software, Visual Studio programming tools, and SQL Server databases.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

Dataconomy

SEPTEMBER 4, 2023

Cloud-based business intelligence (BI): Cloud-based BI tools enable organizations to access and analyze data from cloud-based sources and on-premises databases. Define data ownership, access controls, and data management processes to maintain the integrity and confidentiality of your data.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

MARCH 3, 2025

Essentially, BI bridges the gap between raw data and actionable knowledge. It gathers information from various sources sales databases, marketing platforms, customer feedback, and more and consolidates it into a unified view. Ensuring data accuracy and consistency through cleansing and validation processes.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

phData

AUGUST 29, 2023

In a perfect scenario, everything a data analyst would need to answer business users’ questions would live in cleaned, curated, and modeled tables in a data warehouse. The analyst could connect to the data warehouse and start developing reports.

Power BI 52

Power BI Data Warehouse Database Data Analyst 52

phData

JANUARY 9, 2025

JSON (JavaScript Object Notation) is a popular data format for exchanging information between servers and web applications. Its lightweight and readable structure makes it a preferred choice for many developers and data analysts. We will use a table from the Sigma Sample Database. Snowflake).

Data Warehouse 52

Data Warehouse Database Data Analyst 52

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Data Warehouse 52

Data Warehouse Data Lakes Data Governance Analytics 52

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Warehousing: Amazon Redshift, Google BigQuery, etc. Read more to know.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Alation

MARCH 1, 2022

Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC. Technical users may wonder: How are such advancements possible?

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling. Knowledge of tools like D3.js

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Alation

APRIL 19, 2022

Data producers and consumers alike are working from home and hybrid locations more often. And in an increasingly remote workforce, people need to access data systems easily to do their jobs. This might mean that they’re accessing a database from a smartphone, computer, or tablet. Today, data dwells everywhere.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

Pickl AI

DECEMBER 10, 2024

Summary: Oracle’s Exalytics, Exalogic, and Exadata transform enterprise IT with optimised analytics, middleware, and database systems. These cutting-edge solutions optimise analytics, middleware, and database performance , enabling businesses to achieve unparalleled efficiency and scalability.

Database 52

Database Analytics Analytics Business Intelligence 52

Pickl AI

JUNE 28, 2023

Schema Integration Schema integration deals with reconciling data stored in different database schemas or structures. It involves mapping and transforming data elements to align with a unified schema. It ensures that the integrated data is available for analysis and reporting.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

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.

SQL 52

SQL Data Warehouse Analytics Analytics 52

phData

MARCH 1, 2024

This process introduces considerable time and effort into the overall data ingestion workflow, delaying the availability of data to end consumers. Fortunately, the client has opted for Snowflake Data Cloud as their target data warehouse. The Snowflake account is set up with a demo database and schema to load data.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Alation

JUNE 9, 2021

The explosion in data and database types is a major pain point of the modern data consumer. What is Data Search & Discovery? According to IDC , more than 59 zettabytes (59,000,000,000,000,000,000,000 bytes) of data was created, captured, and consumed in the world in 2020. Today they have too much.

Data Governance 59

Data Governance Database Cloud Data Machine Learning 59

Alation

MAY 24, 2022

By augmenting rich human data curation in Alation with purpose-built data quality from partners, customers will have a complete view into the trustworthiness of data. It is advantageous to data consumers, such as data analysts and data scientists , to connect data quality context into their workflow in Alation.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Alation

AUGUST 30, 2022

Yet it was siloed and locked up in different databases and tools. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This expansive map of tools constitutes today’s modern data stack. In a complex modern data stack, the need for intuitive search grows essential.

Data Governance 52

Data Governance Tableau Data Quality Data Analyst 52

Pickl AI

OCTOBER 19, 2023

Implement Data Validation Rules To maintain data integrity, establish strict validation rules. This ensures that the data entered meets predefined criteria. Implementing validation rules helps prevent incorrect or incomplete data from being added to your databases.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

Pickl AI

JUNE 7, 2024

Also Read: Top 10 Data Science tools for 2024. It is a process for moving and managing data from various sources to a central data warehouse. This process ensures that data is accurate, consistent, and usable for analysis and reporting. This process helps organisations manage large volumes of data efficiently.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

AUGUST 31, 2023

The process of data profiling helps in understanding the structure, content and interrelationships of data. The method makes use of business rules and analytical algorithms to minutely analyse data for discrepancies. Identify potential foreign key relationships between tables in a relational database.

Data Profiling 52

Data Profiling ETL Data Quality Data Wrangling 52

phData

JUNE 3, 2024

The Snowflake team can use Fail Safe to restore your data in the event of an extreme operational failure, giving you even more peace of mind. It allows you to CLONE an object (table, schema, or even an entire database) to make a complete copy of it. Zero Copy Cloning Zero Copy Cloning is another feature that’s as fun as handy.

Machine Learning 52

Machine Learning Machine Learning Database Cloud Data 52

IBM Journey to AI blog

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. The existing Data Catalog becomes the Default catalog (identified by the AWS account number) and is readily available in SageMaker Lakehouse.

SQL 137

SQL Data Analyst Data Warehouse AWS 137