Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Astera

FEBRUARY 1, 2024

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?

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Data Modelling Retail Documentation Visualization 40

Dataversity

JUNE 19, 2023

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

Monitoring 130

Monitoring Data Modelling Data Quality Data Governance 130

Sisense

JULY 6, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive.

Data Management 98

Data Management Data Architecture Data Governance Government 98

Sisense

OCTOBER 14, 2020

Here, we focus on the role of the data team in successfully applying advanced analytics and ensuring that you get the most from your data to make your organization truly data-driven. Smart organizations already appreciate the power of data and its influence on building successful strategies. Everyone wins!

Data Modelling 98

Data Modelling Embedded Analytics Data Warehouse Innovation 98

Dataversity

MAY 1, 2023

Many organizations have mapped out the systems and applications of their data landscape. Many have modeled their data domains and key attributes. The remainder of this point of view will explain why connecting […] The post Connecting the Three Spheres of Data Management to Unlock Value appeared first on DATAVERSITY.

Data Management 244

Data Management Documentation Data Modelling Data Quality 244

Astera

AUGUST 30, 2024

In this blog, you will learn about on-premise to cloud migration, its different types, challenges, and best practices. An on-premise to cloud migration entails moving infrastructure and data from an on-premise system (third-party data centers or infrastructure housed locally) to the cloud (public, private, or hybrid).

Data Governance 52

Data Governance Government Data Quality Documentation 52

Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

Data Management 244

Data Management Agile Data Warehouse Data Modelling 244

Astera

MARCH 28, 2024

So, organizations create a data governance strategy for managing their data, and an important part of this strategy is building a data catalog. They enable organizations to efficiently manage data by facilitating discovery, lineage tracking, and governance enforcement.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

JULY 3, 2024

It creates a space for a scalable environment that can handle growing data, making it easier to implement and integrate new technologies. Moreover, a well-designed data architecture enhances data security and compliance by defining clear protocols for data governance.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Sisense

SEPTEMBER 12, 2019

We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company , whether they know it or not. Do you need to work on creating more data governance or put more effort on training and documentation? #5

Documentation 81

Documentation Government Business Intelligence Business Intelligence 81

Whizlabs

MARCH 14, 2021

Data modelling and visualizations. As a business reporter, Power BI will make it easier for you to connect and integrate the data. Moreover, it will create clean and specified data models and graphs. It’s one of the most effective tools if you are a data analyst. Security and administration.

Visualization 52

Visualization Cloud Computing Data Modelling Monitoring 52

Astera

JANUARY 2, 2024

When data is organized and accessible, different departments can work cohesively, sharing insights and working towards common goals. Data Governance vs Data Management One of the key points to remember is that data governance and data management are not the same concepts—they are more different than similar.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Astera

FEBRUARY 28, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Ntara

MAY 18, 2021

You can expect a constant back-and-forth as attributes are added and the data model—which both systems have to be aware of—is adjusted. As much as you can, we recommend having your product data standardized and enriched before moving ahead with either inRiver or Salesforce. Subscribe to our blog. May 18, 2021. file under.

Innovation 52

Innovation Data Governance Customer Experience Customer Experience 52

Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel. Click to learn more about author Tejasvi Addagada.

Business Intelligence 147

Business Intelligence Business Intelligence Data Discovery Data Modelling 147

Astera

AUGUST 13, 2024

This flexibility supports adding new data sources and services, ensuring the infrastructure can grow alongside the business. Regulatory Compliance Data modernization enhances compliance with current regulations and standards. Step 5: Develop a Data Governance Framework Establish data governance policies and procedures.

Data Governance 52

Data Governance Data Architecture Data Quality Real-time Data 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Data Pine

SEPTEMBER 29, 2022

Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

Data Quality 96

Data Quality Monitoring Big Data Government 96

Astera

MAY 13, 2024

This blog offers an in-depth look at data aggregation to help you understand what it is, how it works, and how it benefits your business when done right. Understanding Data Aggregation What is Data Aggregation? Enhance Data Quality Next, enhance your data’s quality to improve its reliability.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Domo

JANUARY 30, 2024

To help people make timely data-driven decisions, your BI tool needs to be strong in several key product areas, such as: Data visualization Data source integration Warehousing Data transformation Data governance Machine learning and NLP But most tools aren’t strong in all six, or companies lack the resources to enable each component effectively.

Visualization 52

Visualization Documentation Data Governance Data Visualization 52

Dataversity

FEBRUARY 17, 2021

Click to learn more about author Steve Zagoudis. Successful problem solving requires finding the right solution to the right problem. We fail more often because we solve the wrong problem than because we get the wrong solution to the right problem.” – Russell L.

Data Warehouse 130

Data Warehouse Data Modelling Data Governance Data Quality 130

Astera

JULY 13, 2023

Master Data Management (MDM) Master data management is a process of creating a single, authoritative source of data for business-critical information, such as customer or product data. One of the key benefits of MDM is that it can help to improve data quality and reduce errors.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

Dataversity

SEPTEMBER 28, 2022

Data engineering is a fascinating and fulfilling career – you are at the helm of every business operation that requires data, and as long as users generate data, businesses will always need data engineers. The journey to becoming a successful data engineer […]. In other words, job security is guaranteed.

Data Modelling 130

Data Modelling Data Architecture Data Governance Government 130

Dataversity

MARCH 18, 2022

Redman) served as the judge in a mock trial of a data architect (played by Laura Sebastian Coleman) […]. The post What Data Practitioners Need to Know (and Do) About Common Language appeared first on DATAVERSITY. Weinberg [1] In March 2019, one of us (Thomas C.

Chief Data Officer 130

Chief Data Officer Digital Transformation Data Governance Data Modelling 130

Dataversity

JULY 12, 2021

In my eight years as a Gartner analyst covering Master Data Management (MDM) and two years advising clients and prospects at a leading vendor, I have seen first-hand the importance of taking a multidomain approach to MDM. Click to learn more about author Bill O’Kane.

Master Data Management 130

Master Data Management Data Management Data Quality Data Governance 130

Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […]. Click to learn more about author Wayne Yaddow.

Data Warehouse 130

Data Warehouse Data Governance Data Modelling Data Quality 130

Astera

AUGUST 16, 2024

Still, Gartner reports that only 17% of initiatives involving data migration are completed within their budgets or set timelines. Understanding these data migration challenges is the first step toward overcoming them. In this blog, we’ll explore data migration and its different types, challenges, and strategies for dealing with them.

Digital Transformation 52

Digital Transformation Planning Government Cloud Computing 52

Domo

OCTOBER 22, 2021

Such an offering can also simplify and integrate data management on a massive scale—whether that data lives on premises or in cloud environments—and be used to develop an enterprise-wide data modeling process. The post Why CIOs Should Weave Data Fabrics Into Their Orgs first appeared on Blog.

Data Warehouse 52

Data Warehouse Embedded Analytics Government Digital Transformation 52

Astera

DECEMBER 22, 2022

It’s one of the three core data types, along with structured and semi-structured formats. Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. This makes managing unstructured data difficult.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

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.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

FEBRUARY 16, 2024

You can also schedule, monitor, and manage your data pipelines from a centralized dashboard, ensuring that Finance 360 pipelines are always up-to-date and reliable. You can access and ingest data from any source and system, regardless of the data’s location, format, or structure.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

Astera

JANUARY 25, 2024

Reverse ETL, used with other data integration tools , like MDM (Master Data Management) and CDC (Change Data Capture), empowers employees to access data easily and fosters the development of data literacy skills, which enhances a data-driven culture.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

JUNE 3, 2024

In just the last two years , 90% of the world’s data has been created, and the volume of global data doubles every two years. All this data is stored in databases. Data needs Data structure: Analyze the type of data the organization needs to store—structured, semi-structured, or unstructured.

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 52

Astera

JANUARY 18, 2024

As far as the destinations are concerned, Fivetran supports data warehouses and databases, but it doesn’t support most data lakes. It also offers limited data transformation capabilities and that too through dbt core, which is an open source tool.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

The BAWorld

NOVEMBER 22, 2021

Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Conceptual Data Model. Logical Data Model : It is an abstraction of CDM. Data Profiling.

Data Analytics 98

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