Grace  Lesch

Grace Lesch

1622717118

Manipulating Geo Coordinate Data Using DAO Design Pattern in Jedis

In this article, we are going to learn how to add geocoordinate data and retrieve it using the DAO design pattern. The DAO pattern is implemented as a layer between the client application and the database.

The data being stored in the Redis database is modeled as a domain object (POJO class). It will have only getter and setter methods. The client application knows only the domain object and high-level API.

#database #redis #jedis #dao #geo

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Manipulating Geo Coordinate Data Using DAO Design Pattern in Jedis
 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Grace  Lesch

Grace Lesch

1622717118

Manipulating Geo Coordinate Data Using DAO Design Pattern in Jedis

In this article, we are going to learn how to add geocoordinate data and retrieve it using the DAO design pattern. The DAO pattern is implemented as a layer between the client application and the database.

The data being stored in the Redis database is modeled as a domain object (POJO class). It will have only getter and setter methods. The client application knows only the domain object and high-level API.

#database #redis #jedis #dao #geo

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Samanta  Moore

Samanta Moore

1623835440

Builder Design Pattern

What is Builder Design Pattern ? Why we should care about it ?

Starting from **Creational Design Pattern, **so wikipedia says “creational design pattern are design pattern that deals with object creation mechanism, trying to create objects in manner that is suitable to the situation”.

The basic form of object creations could result in design problems and result in complex design problems, so to overcome this problem Creational Design Pattern somehow allows you to create the object.

Builder is one of the** Creational Design Pattern**.

When to consider the Builder Design Pattern ?

Builder is useful when you need to do lot of things to build an Object. Let’s imagine DOM (Document Object Model), so if we need to create the DOM, We could have to do lot of things, appending plenty of nodes and attaching attributes to them. We could also imagine about the huge XML Object creation where we will have to do lot of work to create the Object. A Factory is used basically when we could create the entire object in one shot.

As **Joshua Bloch (**He led the Design of the many library Java Collections Framework and many more) – “Builder Pattern is good choice when designing the class whose constructor or static factories would have more than handful of parameters

#java #builder #builder pattern #creational design pattern #design pattern #factory pattern #java design pattern

Gerhard  Brink

Gerhard Brink

1624098900

Big Data Architecture: Layers, Patterns, Use Cases and Tools

Introduction to Big Data Architecture

Big Data Architecture helps design the Data Pipeline with the various requirements of either the Batch Processing System or Stream Processing System. This architecture consists of 6 layers, which ensure a secure flow of data.


Big Data Architecture Layers

  • Data Ingestion Layer
  • Data Collector Layer
  • Big Data Processing Layer
  • Data Storage Layer
  • Data Query Layer
  • Big Data Visualization Layer
  • Data Security Layer
  • Data Monitoring Layer

#big data engineering #blogs #big data architecture: layers, patterns, use cases and tools #big data architecture #use cases and tools #patterns