Knowledge Hut

APRIL 25, 2024

Data Governance Data governance is the process of ensuring that data is trustworthy, accurate, available, and usable. It describes the actions people must take, the rules they must follow, and the technology that will support them throughout the data life cycle.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

SEPTEMBER 26, 2023

Workspace is the platform where power BI developers create reports, dashboards, data sets, etc. Dataset is the collection of raw data imported from various data sources for the purpose of analysis. DirectQuery and Live Connection: Connecting to data without importing it, ideal for real-time or large datasets.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Databand.ai

AUGUST 30, 2023

Unified DataOps represents a fresh approach to managing and synchronizing data operations across several domains, including data engineering, data science, DevOps, and analytics. The goal of this strategy is to streamline the entire process of extracting insights from raw data by removing silos between teams and technologies.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Knowledge Hut

APRIL 23, 2024

Without relying on centralized cloud infrastructure, big data analytics at the edge enable organizations to analyze data in real-time, allowing swift reactions and decision-making. Protection Against Cyber Dangers : Organizations need to be on the lookout for cyber threats and data breaches as the amount and value of data increase.

Big Data 52

Big Data Retail Recruitment Transportation 52

AltexSoft

NOVEMBER 10, 2021

The DW nature isn’t the best fit for complex data processing such as machine learning as warehouses normally store task-specific data, while machine learning and data science tasks thrive on the availability of all collected data. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. They can also design and run data apps and securely share, gather, and commercialize real-time data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 12, 2023

Unstructured data storage solutions must ensure data durability (protection against data loss) and availability (ensuring data is accessible when needed). That’s why there must be some sort of data replication, backup strategies, and failover mechanisms. Data security and privacy.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Monte Carlo

MAY 31, 2023

Companies that leverage CRMs might mitigate risks related to broad domain access by implementing a framework that includes data collection controls, human-error checks, restricted raw data access, cybersecurity countermeasures, and frequent data back-ups.

Building 52

Building Data Validation Healthcare Data Integration 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64