Astera

NOVEMBER 16, 2022

The 2022 Global Hybrid Cloud Trends Report by Cisco shows that 82% of organizations have adopted the hybrid cloud, which isn’t surprising given the growing popularity of hybrid data architectures among modern IT professionals. Understand and assess potential data quality challenges in a hybrid cloud environment.

Data Architecture 52

Data Architecture Data Quality Data Warehouse Data Governance 52

Astera

FEBRUARY 14, 2024

Identify the source systems, data entities, and stakeholders involved. Your Salesforce data migration plan should also be clear about the timelines, resources, and responsibilities. Ensure alignment with Salesforce data models and consider any necessary data cleansing or enrichment.

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Quality 52

Astera

MAY 6, 2024

Healthcare : Medical researchers analyze patient data to discover disease patterns, predict outbreaks, and personalize treatment plans. Data mining tools aid early diagnosis, drug discovery, and patient management. Sisense Sisense is a data analytics platform emphasizing flexibility in handling diverse data architectures.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

FEBRUARY 14, 2024

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. It applies selected business rules, calculations, data cleansing and data quality functions to the data.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Astera

MAY 31, 2024

Here are the critical components of data science: Data Collection : Accumulating data from diverse sources like databases, APIs , and web scraping. Data Cleaning and Preprocessing : Ensuring data quality by managing missing values, eliminating duplicates, normalizing data, and preparing it for analysis.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

DECEMBER 2, 2022

Healthcare data migration involves moving health care data from existing applications and systems, including electronic health record (EHR) systems, to a new destination. Medical data can come from a myriad of sources, including but not limited to: Patient records and healthcare data, comprising demographic and clinical information.

Healthcare 52

Healthcare Documentation Data Quality Data Architecture 52

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Quality 101

Data Quality Data Security Data Architecture Agile 101

Astera

OCTOBER 27, 2023

The “cloud” part means that instead of managing physical servers and infrastructure, everything happens in the cloud environment—offsite servers take care of the heavy lifting, and you can access your data and analytics tools over the internet without the need for downloading or setting up any software or applications.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. Combining datasets is key to unlocking more advanced insights.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

Tableau

SEPTEMBER 23, 2021

Data privacy policy: We all have sensitive data—we need policy and guidelines if and when users access and share sensitive data. Data quality: Gone are the days of “data is data, and we just need more.” Now, data quality matters. Data modeling. Data migration .

Data Governance 91

Data Governance Government Data Quality Change Management 91

Tableau

SEPTEMBER 23, 2021

Data privacy policy: We all have sensitive data—we need policy and guidelines if and when users access and share sensitive data. Data quality: Gone are the days of “data is data, and we just need more.” Now, data quality matters. Data modeling. Data migration .

Data Governance 79

Data Governance Government Data Quality Change Management 79