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Home > Technology >  Big data – Thematic Research

Big data – Thematic Research

Today’s digital economy is powered by data. It is produced in abundance by both individuals and enterprises and stored in vast data centers, some of which cover hundreds of thousands of square feet. Several prominent businesspeople and a number of leading publications have described data as the new oil, capable of generating significant value if used in the right way.

The challenge for enterprises is not collecting data unlike oil, data is not scarce, nor is it difficult to extract but deriving actionable insights from the wealth of information that they accumulate on a daily basis. This is where big data technologies come in, with their ability to handle extremely large, diverse data sets that, when analyzed, can reveal patterns, trends, and associations, especially relating to human behavior and interactions.

“Big data has applications across industries, from providing detailed customer profiles for retailers to improving the drug discovery process through the use of predictive modeling. The opportunities available to those companies that can harness the power of big data are clear and wide-ranging but it is not a one-size-fits-all solution. Instead, businesses need to tailor their approach to their own specific requirements and use cases.” – Cyrus Mewawalla, Head of Thematic Research at GlobalData

Scope

This report focuses on the seven key technologies within the big data theme, and the leaders in each of these technologies:

  • Data democratizations
  • Central Governance
  • Data integration
  • Data privacy and protection
  • AI for data quality
  • AI-ready data
  • Data as a service (DaaS)

It highlights the main trends over the next 12 to 24 months, classifying these trends into five categories data trends, technology trends, data center trends, macroeconomic trends, and regulatory trends.

The report also provides an industry analysis and examines the big data value chain.

It uses scorecards to identify the leading companies in a sector.

It offers a technology briefing of how big data combines traditional data management technologies with new forms of data processing that are better suited to modern formats.

Key Highlights

Big data has emerged in response to the exponential growth in data, which is itself the result of a combination of technology trends, including (but not limited to) the ubiquity of mobile devices (including smartphones and tablets), widespread use of social media, and the rise of the IoT.

The opportunities available to those companies that can harness the power of big data are clear and wide-ranging but it is not a one-size-fits-all solution. Instead, businesses need to tailor their approach to their own specific requirements and use cases.

Too much data is scattered across too many formats. This data is only valuable to businesses and consumers if it can be analyzed accurately and efficiently. For instance, streamed data – which is data in motion – can create business opportunities if analyzed quickly enough. An online retailer, for example, can use big data to make a recommendation to a customer while the customer is browsing the online store. Businesses are willing to pay good money for these types of revenue-enhancing opportunities.

A dramatic growth in data volumes means that not only do processors have to advance to be capable of processing all of the data that is being generated, but there also need to be improvements in storage systems, networks, and approaches to data security and governance.

 

Reasons to Buy

Big data has applications across industries, from providing detailed customer profiles for retailers to improving the drug discovery process through the use of predictive modeling.

This report analyzes the opportunities available to companies that harness the power of big data.

It also highlights the need to tailor their approach to their own specific requirements and use cases.

Companies that fail to derive actionable insights from the wealth of data that they possess will struggle to compete with rivals using diverse data sets to gain a deeper understanding of their customers and marketplace.

Companies Mentioned

Alphabet

Alteryx

Amazon

Artista Networks

Cisco

Cloudera

FICO

HPE

IBM

Intel

Micron

Microstrategy

Nvidia

Oracle

Salesforce

SAP

Software AG

Tableau Software

Talend

VMware

Dataiku

Data virtuality

Delphix

Denodo Technologies

Informatica

Logi Analytics

MarkLogic

PostgreSQL

Qlik

RapidMiner

Reltio

TIBCO

Table of Contents

Players

Technology briefing

Trends

Industry analysis

Value chain

Companies

Sector scorecards

Glossary

Methodology

    Pricing

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