Blog Data Management Data Requirement Visualization 
Astera
APRIL 28, 2023
With the ever-increasing volume of data generated and collected by companies, manual data management practices are no longer effective. Artificial intelligence (AI) and intelligent systems have significantly contributed to data management, transforming how organizations collect, store, analyze, and leverage data.
The BAWorld
MARCH 13, 2024
Research conducted by the Project Management Institute, reveals that in significant organizations, specialists dedicate approximately 83% of their time to applying and executing various business analysis methodologies. It ensures data consistency, accessibility, and integrity, facilitating efficient data storage, retrieval, and analysis.
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Astera
JANUARY 18, 2024
So, in case your data requires extensive transformation or cleaning, Fivetran is not the ideal solution. Fivetran might be a viable solution if your data is already in good shape, and you need to leverage the computing power of the destination system. You can easily design and orchestrate complex workflows.
Astera
JULY 18, 2023
They enable data professionals to clean, transform, and organize raw data efficiently, saving countless hours of manual work while ensuring data quality and consistency. In this blog, we will explore the benefits of data wrangling tools and the top contenders in the market.
Data Pine
MAY 2, 2023
To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? Financial efficiency: One of the key benefits of big data in supply chain and logistics management is the reduction of unnecessary costs. Now’s the time to strike.
Astera
OCTOBER 19, 2023
Manual export and import steps in a system can add complexity to your data pipeline. When evaluating data preparation tools, look for solutions that easily connect data visualization and BI reporting applications to guide your decision-making processes, e.g., PowerBI, Tableau, etc. Top 5 Data Preparation Tools for 2023 1.
Astera
JANUARY 23, 2024
Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.
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