Kaira P

1622042351

Tackling unstructured data with intelligent document processing

Various estimates indicate that 80% of enterprise data is unstructured and it is difficult to automate processes having unstructured data with traditional automation tools. There is a rising need for …

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 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

Ian  Robinson

Ian Robinson

1623981720

Tackling unstructured data is the only way to deliver digital transformation

Getting data management right is vital for data driven growth

As the volume of data continues to grow, and businesses’ desire to make that data work for them, the only way to enhance business outcomes and drive innovation, is to recognise the need to improve how they manage unstructured data, this is according to Simon Bain, CEO, OmniIndex.

“Organisations need to focus head-on into the challenge of unstructured data, now more important than ever with the growth of the multi-cloud environment and the ongoing issue of data silos. IT departments must find a solution to this issue and make the information that is very often hidden in unstructured formats available to business leaders.

“Far too often data is dispersed throughout an enterprise with no one single view and while many talk about the concept of data consolidation, the reality is very different with multiple silos and in widely different formats. Data driven growth is therefore being held back.”

Bain contends that poor data management, the lack of integration between structured and unstructured data and a fundamental lack of collaboration between data teams will hinder businesses looking to grow.

“This leads ultimately to a low return for data analytics and even business intelligence because you are simply not seeing the complete picture. Managing data is highly complex and is a huge challenge when it is hidden from view. But getting this right is a massive step in business transformation,” added Bain.

OmniIndex is a new simple-to-implement SaaS solution that enables access to unstructured data and is the first that addresses all areas of unstructured data analytics: AI Contextual Awareness, AI Sentiment Analysis, Automatic Content Analysis and PII Alerting. It is a simple to implement SaaS solution with a powerful AI engine.

As a result, the enterprise can view detailed analytics on the hidden data that sprawls across applications and siloes that invariably houses the day-to-day momentum of that business. That means addressing the ‘Other 80%’ of data hidden and inaccessible.

“For agile organisations this means access to valuable data previously unavailable. For example, data on customer sentiment that enables organisations to spot issues and trends, increase customer retention, and innovate faster.’

“There is no doubt that the pandemic has acted as an agent of change as organisations look to adapt and innovate. Now is the time to put in place a solution that delivers a single view of data, a management solution that empowers an organisation to make quicker, more informed decisions based on the facts!” concluded Bain.

#big data #latest news #unstructured data #tackling unstructured data is the only way to deliver digital transformation #tackling unstructured data #deliver digital transformation

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

 iOS App Dev

iOS App Dev

1622608260

Making Sense of Unbounded Data & Real-Time Processing Systems

Unbounded data refers to continuous, never-ending data streams with no beginning or end. They are made available over time. Anyone who wishes to act upon them can do without downloading them first.

As Martin Kleppmann stated in his famous book, unbounded data will never “complete” in any meaningful way.

“In reality, a lot of data is unbounded because it arrives gradually over time: your users produced data yesterday and today, and they will continue to produce more data tomorrow. Unless you go out of business, this process never ends, and so the dataset is never “complete” in any meaningful way.”

— Martin Kleppmann, Designing Data-Intensive Applications

Processing unbounded data requires an entirely different approach than its counterpart, batch processing. This article summarises the value of unbounded data and how you can build systems to harness the power of real-time data.

#stream-processing #software-architecture #event-driven-architecture #data-processing #data-analysis #big-data-processing #real-time-processing #data-storage

Sid  Schuppe

Sid Schuppe

1617955288

Benefits of Data Ingestion

In the last two decades, many businesses have had to change their models as business operations continue to complicate. The major challenge companies face today is that a large amount of data is generated from multiple data sources. So, data analytics have introduced filters to various data sources to detect this problem. They need analytics and business intelligence to access all their data sources to make better business decisions.

It is obvious that the company needs this data to make decisions based on predicted market trends, market forecasts, customer requirements, future needs, etc. But how do you get all your company data in one place to make a proper decision? Data ingestion consolidates your data and stores it in one place.

#big data #data access #data ingestion #data collection #batch processing #data access layer #data integration platform #automate data collection